AI Weekly: Open Weights Surge and a Breaking Claude API

Week of October 14-21, 2026

The big frontier launches landed just before this window. Claude Haiku 5.5, GPT-6 in ChatGPT, Meta Muse Wonder and Gemini 4 Argon all shipped between October 7 and October 13. This week was about what came after: a wave of open-weight models, a breaking Claude API version, a round of model retirements and an NVIDIA keynote that put supply chains ahead of chips.

Here is what changed, what it costs and what you need to do about it.

Models: Meta Muse Spark Open Leads an Open-Weight Week

No new closed frontier flagship shipped between October 14 and October 21. The open-weight side made up for it. Meta, NVIDIA, DeepSeek, MiniMax, Mistral and Tencent all released models or weights in the same seven days. For teams that self-host or fine-tune, this was the busiest week of the quarter.

Meta Muse Spark Open (October 15)

Meta released Muse Spark Open on October 15. The model ID on Hugging Face is meta-models/Muse-Spark-Open-816B-A42B. It is a mixture-of-experts model with 816 billion total parameters and 42 billion active per token. Context reaches 1 million tokens. Meta did not publish a max output figure.

The model is natively multimodal. Press coverage describes text, image, video and audio input with text output. Meta ships weights in BF16, and coverage also reports an NVFP4 build. Day-one engine support covers SGLang, vLLM, TensorRT-LLM, Transformers, MLX, llama.cpp and Unsloth.

Distribution is wide. Weights are on Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden and Microsoft Foundry. Hosted APIs are live on Baseten, Fireworks, Groq, Modal, Nebius, OpenRouter and Together. Meta also demoed the model on two linked M5 Ultra Mac Studios. That is a useful signal for anyone sizing on-prem hardware.

Two caveats matter. First, Meta published no per-token price, so cost depends on the host you pick. Second, the license is the "Muse Model License," not Apache 2.0 or MIT. Meta describes it as carrying "limited commercial terms." One third-party reading says API resellers above $20 million in gross revenue need a separate deal with Meta. That reading is unconfirmed, so check with your legal team before building a business on it.

Meta calls Muse Spark Open "the most capable US open-weight model to date." Its blog gives no benchmark scores to back that claim. Artificial Analysis, an independent evaluator, scored it 39 on its Intelligence Index, according to press reports. That puts it behind MiMo-V2.6-Pro at 46 on the same index.

The strategic story is bigger than the score. Meta's previous flagship, Muse Spark, was closed. Muse Spark Open marks a partial return to the open-weight playbook that made Llama popular. For lakehouse teams running agents next to governed data, a 1M-context open model with broad engine support is a real option for private deployments.

NVIDIA Nemotron 3.5 Super VL and Bolt (October 15)

NVIDIA expanded the Nemotron family on the same day. The headline model is Nemotron 3.5 Super VL, a 120B-A12B vision-language mixture-of-experts model built for agents. NVIDIA trained it on about 26 trillion tokens, then added about 3.8 million post-training samples and a reinforcement learning stage.

NVIDIA says Super VL comes close to its largest reasoning model at about one-fifth the parameters. It also claims up to 5x the throughput of the next-best open model in its class, citing an Artificial Analysis chart. Treat that 5x as vendor-reported. HPCwire reports a score of 26.5 on the Artificial Analysis Intelligence Index, plus a context of up to 1M tokens and the OpenMDW-1.1 license. NVIDIA's own blog states neither the context nor the license, so confirm both on the model card before you deploy.

The more interesting release for many readers is Nemotron 3.5 Bolt 74B-A9B. NVIDIA trained it with native 2-bit quantization so the full model fits in 24GB of memory. That targets RTX desktops, DGX Spark and the new RTX Spark laptops. It runs on llama.cpp, Ollama, LM Studio, Unsloth and vLLM.

NVIDIA claims Bolt ranks first among open models in its class on PinchBench and second on BrowseComp. Both rankings are vendor-reported. Press reports put Bolt at 21.4 on the Artificial Analysis Intelligence Index. A smaller Bolt E4B that fits in 4GB is due October 23.

Super VL is available on Hugging Face, OpenRouter, ModelScope and NVIDIA NIM. If you need an agent model that reads screenshots and documents on your own GPUs, it belongs on your test list.

DeepSeek-V4.1-Flash-1017 and Search & Fetch APIs (October 17)

DeepSeek shipped a refreshed V4.1 Flash on October 17. The model ID is deepseek-ai/DeepSeek-V4.1-Flash-1017. Hugging Face metadata lists 763 billion total parameters. One secondary source said 552 billion, so trust the Hugging Face figure. Context is 1M tokens, and the weights carry an MIT license.

The gains over the September build are large on agent and coding tasks. These numbers come from DeepSeek's model card, so they are vendor-reported:

DeepSeek's own table lists Claude Opus 5 at 74.0 on DeepSWE v1.1. That puts the new Flash snapshot ahead on that one test, by DeepSeek's count. Wait for independent runs before you treat that as settled.

Pricing is murky. DeepSeek's announcement shows prices only in an image. A secondary source says pricing is unchanged at $0.15 input and $0.60 output per million tokens off-peak, and $0.30 and $1.20 at peak. We did not find those figures in a text source, so check the DeepSeek console.

The second launch matters as much as the model. DeepSeek opened its Search and Fetch APIs to all users at $0.75 per 1,000 calls per endpoint. Calls are free through server-side tools in DeepSeek Harness, Claude Code and Codex until October 31 at 16:00 UTC. Model labs now sell the tools around the model, not just the tokens.

MiniMax M3.1 Flash (October 19)

MiniMax released M3.1 Flash on October 19 under the model ID MiniMax-M3.1-Flash. It had circulated as "Space Bunny" since late September. Pricing is $0.15 per million input tokens, $0.60 per million output tokens and $0.015 per million cached input tokens.

MiniMax says the model costs 70% less on agentic tasks than its predecessor. It also claims about 3x the speed, with 200+ tokens per second at peak and 170+ at the median. MiniMax did not state a context window. One gateway lists 1M tokens.

The vendor-reported scores lean hard toward agents:

• DeepSWE v1.1: 73.7%
• OSWorld V2: 61.7
• Agents' Last Exam: 29.6
• BankerToolBench: 76.2
• CyberGym: 82%

The model is live on the MiniMax API, the M Plan and MiniMax Code. MiniMax says weights "will be released later." Reports point to October 23, but that date is unconfirmed.

Note the pricing pattern. MiniMax M3.1 Flash and the reported DeepSeek off-peak rate both sit at $0.15 in and $0.60 out. Fast agent-grade models are converging on a price floor. That changes the math on running agents over large datasets.

Mistral Timestral, Tencent Hy-Memory and Grok Voice 3.0

Three smaller releases deserve a note.

Mistral released Timestral on October 15. It is a family of time-series forecasting models in 5M, 28M, 123M and 209M sizes under a modified MIT license. Context is 32,768 steps with a 1,024-step forecast horizon. Mistral reports the 209M model ranks first on GIFT-Eval, with a MASE of 0.658 and CRPS of 0.446, plus first place on TIME and fev-bench. Those rankings are vendor-reported. The model runs on CPU, and Mistral says a 209M forecast took 140 milliseconds on 8 threads.

Timestral is worth a look for data teams. Forecasting on lakehouse tables usually means exporting data to a separate ML stack. A 209M model that runs on CPU in milliseconds can sit much closer to the query engine.

Tencent posted Hy-Memory-30B-A3B to Hugging Face on October 15. It is a memory-writer model with about 3 billion active parameters under Apache 2.0. Its job is to decide what an agent should remember between sessions. Tencent reports a cross-harness average of 55.49, against 54.62 for Claude Opus 5. That comparison is vendor-reported.

xAI shipped Grok Voice 3.0 as grok-voice-3.0 at $0.08 per minute. If you call the grok-voice-latest alias, you are now on 3.0, and version 2.0 is deprecated. Press reports put it at 86.9 on the Artificial Analysis speech-to-speech index, up from 81.3. Latency rose from 0.70 seconds to 0.81 seconds. Pin your version if latency matters to your app.

Claude API Version 2026-10-21 Breaks Old Calls (October 21)

The most important model-platform change this week was not a model. Anthropic shipped API version 2026-10-21 along with new major versions of every official SDK. The new SDKs send the new version header by default. If you upgrade your SDK without reading the migration guide, some calls will fail.

Here are the new SDK versions:

• Python 2.0.0
• TypeScript 1.0.0
• C# 13.0.0
• Go 2.0.0
• Java 3.0.0
• PHP 1.0.0
• Ruby 2.0.0
• ant CLI 2.0.0

The SDKs and CLI also move from the MIT license to Apache 2.0.

Three request patterns now return a 400 error under the new version. First, sending temperature, top_p or top_k fails, even at default values. Second, a document block placed directly in an assistant message fails. Third, a user text block with non-empty citations fails. Workloads that need sampling parameters can stay on the 2023-06-01 version for now.

The SDK changes go further. Text Completions is gone from the TypeScript, Go, Java and Ruby SDKs and from the CLI. API keys now travel as Authorization: Bearer, so check any proxy that inspects the old header. Each client now holds one credential, resolved in a fixed order: ANTHROPIC_API_KEY, then ANTHROPIC_AUTH_TOKEN, then the profile, then workload identity federation. The ant CLI drops its --api-key and --auth-token flags. The Admin API drops old field names and replaces workspace_id on API keys with scope.

The practical advice is simple. Pin your SDK version in CI today. Then upgrade on a branch, run your test suite and fix the 400s before you ship. The full release notes list every change.

Other Anthropic Updates

Anthropic made several smaller changes in the same week.

• October 14: OpenTelemetry export entered beta, and Managed Agents gained scheduled deployments on Claude Platform on AWS.
• October 15: Opus 5.5 fast mode left research preview. It no longer needs a beta header, gets default rate limits and is available on Microsoft Foundry.
• October 15: The Models API now reports whether each model supports thinking: {type: "between_tools"}, which turns off up-front thinking and lets the model think only between tool calls.
• Retirement: Claude Sonnet 4.5 retires on November 30. The replacement is claude-sonnet-5-5.

On the policy side, Anthropic published an update on independent evaluators on October 15. METR now has employee-like access, with six staff onboarded and the right to publish. SecureBio is reviewing the chemical and biological chapter of Anthropic's August Risk Report. Outside review with publication rights is a meaningful step for frontier lab transparency.

Retirements Across Codex and Copilot

Model retirements hit two major coding platforms.

OpenAI retired GPT-5.5 in Codex on October 14 for users signed in with ChatGPT. API-key sessions are not affected. The replacement is gpt-6.1-sol.

GitHub deprecated six Copilot models on October 19:

GitHub also announced a second round for November 16. Claude Opus 4.8 and Opus 5 move to Opus 5.5. GPT-5.6 Terra moves to GPT-6.1 Sol or GPT-6 Luna. If your team pins models in Copilot policies, update those policies before mid-November.

What This Means for Practitioners

Three patterns stand out. Open-weight models now ship with 1M context, broad engine support and hosted APIs on day one. Fast agent models are settling at $0.15 in and $0.60 out per million tokens. And platform churn is real: in one week you got a breaking API version, eight model retirements and an alias that silently moved to a new voice model. Pin versions, track deprecation pages and budget time each month for upgrades.

Tooling: Approval Modes, Credentials and Multi-Model Coding

Coding agents had a security-heavy week. The common theme was control. Vendors tightened who approves an agent's actions, how credentials flow and how long tokens live.

Claude Code 2.1.299 Through 2.1.306

Claude Code shipped eight releases between October 14 and October 21, according to npm. The changelog shows the bulk of the work went into approval modes and permissions.

On approval modes, a new /auto-mode-setup command walks you through auto mode, which now works on more providers. Headless claude -p runs and SDK sessions now start in default mode on third-party providers. That is a safer starting point for CI pipelines. A new CLAUDE_CODE_AUTO_MODE_MODEL variable sets which model classifies actions in auto mode. And a check can now carry decider: "person", which means only a human can approve it.

Observability improved too. OpenTelemetry tool_decision events now include classifier_verdict and permission_mode. Security teams can now see why an agent action was allowed, not just that it happened.

Several permission rules got stricter:

• MCP allow rules now match only the server they name.
• Hooks in Cowork cloud sessions can no longer change the permission mode.
• A new sandbox.allowNestedUserNamespaces setting exists, and the changelog warns that it can bypass sandbox file protections. Leave it off unless you know why you need it.
• allowedMcpServers no longer filters some managed servers. Admins should use deniedMcpServers to block servers.

Credential fixes landed for forceLoginOrgUUID and MDM login settings, plus a login bug in cloud -p runs.

Billing and usage got clearer warnings. Idle compaction now runs for conversations over 200K tokens that sit idle for about 54 minutes. New /usage warnings appear, and Pro and Max users see a warning before resuming an idle conversation that eats a noticeable share of the 5-hour limit. Prompt suggestions are skipped after replies billed to credits.

One fix will save some people real pain. The --worktree flag no longer silently deletes a worktree and its branch at exit. New /advisor and /claude-api managed-agents-secure commands round out the releases.

Codex CLI 0.163.0 (October 15)

OpenAI shipped Codex CLI 0.163.0 on October 15. The feature list is practical:

• A searchable /config screen
• Steering Codex while it is mid-response
• A leader key in /keymap
• A /daemon command that restarts the background server
• Parallel read-only tool calls

A feature called "Daybreak" is now on by default for eligible accounts. The release notes do not explain what it does.

The security fixes matter more. Resumed threads now restore their permissions and network approvals, so a resumed session no longer starts with stale or missing grants. The network proxy now checks permission before the DNS lookup and blocks credential-alias bypasses. New sandbox integrity checks run on Linux with bubblewrap, macOS with Seatbelt and Windows with MXC. Codex also stopped bundling its patched zsh. On the model side, Codex now advertises Ultrafast mode for GPT-6.1 Sol on Amazon Bedrock.

GitHub Copilot HydraFusion Max (October 14)

GitHub updated HydraFusion and added a HydraFusion Max option in research preview. HydraFusion combines several models into one answer. The model pool is Claude Opus 5.5, GPT-6 Astra, GPT-6.1 Sol and GPT-6 Luna.

Drafts run at medium reasoning effort and reviews run at high effort. A new "Cascade" judging step asks for a repair only when the judge finds a problem. Critique now uses several critic models in parallel. HydraFusion works in VS Code, the Copilot app and Copilot CLI on the Pro, Pro+, Business and Enterprise plans.

One gap stands out. GitHub's post does not explain how HydraFusion Max bills premium requests. Several models per answer means several model calls per answer. Check your usage dashboard before you turn it on for a whole org.

GitHub shipped more on October 15. Agentic autofix for code scanning is now generally available. AI Scan for pull requests also reached GA, and Copilot in Slack and Teams gained multi-repo support. On October 19, GitHub released a model policy REST API at the enterprise, team, agent-app and org levels. Platform teams can now manage model access as code instead of clicking through settings.

GitHub Universe runs October 28-29. Expect more Copilot news there.

GitHub CLI 2.103.0: Expiring Tokens (October 21)

GitHub CLI 2.103.0 added opt-in OAuth tokens that expire and refresh on their own. GitHub says a leaked token "becomes unusable within hours." That is a big deal now that coding agents call gh on your behalf all day.

You opt in with gh auth login --expiring or gh config set expiring_credentials enabled. Scripts that cache the output of gh auth token will break, so update those first. The feature needs GitHub Enterprise Server 3.23 or later. GitHub plans to make it the default for new sign-ins in a future release.

GitHub also put a package firewall into public preview on October 20.

Cursor Canvases and Environments API (October 16)

Cursor's October 16 update lets cloud agents build canvases that you can share by link. An Environments API entered beta. Environments now support up to 300 repositories, and large ones load 5x faster, by Cursor's count. Cursor made no pricing changes.

Claude Platform: Per-Customer Safety Controls

Anthropic shipped two features for teams that build agents for their own customers. On October 20, user profiles arrived at /v1/user_profiles. They scope safety enforcement to one end customer instead of your whole organization. One bad actor in your app no longer puts your whole API account at risk.

The same day, organization webhooks entered beta. They fire when a user profile is restricted or banned. Inference hooks reached general availability. On October 14, Managed Agents web_search started following org-level domain restrictions.

These are the kinds of controls that make agents safe to put in front of paying customers. If you run a multi-tenant agent product, user profiles belong in your next sprint.

Quiet Week Elsewhere

We found nothing dated in this window from Google Antigravity, Gemini CLI, Devin Desktop or Kiro. Expect that to change as GitHub Universe and AGNTCon approach.

Standards: MCP Reorganizes Its Working Groups

Standards had the thinnest week of the four sections. No new MCP spec version shipped. A2A had no release, and the Agentic AI Foundation published no press releases in the window. The news came from governance, adoption data and identity.

MCP Creates a Tasks and Events Working Group (October 20)

The Model Context Protocol (MCP) is the open standard that lets AI apps connect to tools and data sources through one interface. On October 20, the project merged SEP PR #3440. It folds the task work and the event and trigger work into one new Tasks and Events Working Group.

The same change turns the Agents Working Group into an Interest Group. Interest Groups discuss ideas but have no decision rights. The message is clear. MCP's core team wants long-running tasks and event-driven triggers designed together, not in two separate rooms.

For context, the current spec is still version 2026-07-28. That release removed the initialize handshake and the Mcp-Session-Id header. It also deprecated Roots, Sampling and Logging. The latest SDKs are Python 2.3.0, released October 2, and TypeScript 2.3.1, released October 5. The MCP registry sits at version 1.8.1 and remains in preview.

Why does a tasks-and-events group matter to data teams? Most data work is not a single request and response. A pipeline run, a table compaction or a long query is a task that finishes later. Agents need a standard way to start that work, check on it and get told when it is done. This working group is where that standard will come from.

Skills Over MCP: Adoption Is Still Thin (October 21)

API Evangelist published an adoption study on October 21. The author probed 9,170 MCP endpoints. Only four providers serve skills the way the Skills Extension spec describes. Those four are Hugging Face, Glean, Renoolab and BestPrice. The Skills Extension, SEP-2640, reached Final status on September 13.

The protocol version data is even more telling:

Only 44 responding endpoints run the current spec. More than 500 still run a version from November 2024. That is a big gap between what the spec says and what servers in the wild support. If you build an MCP client, plan to support older protocol versions for a long time. If you run an MCP server, the July 2026 changes are worth the upgrade.

Agent Identity and Credentials

Agent identity did not get a new standard this week, but several vendors shipped identity features. Read together, they show where the industry is heading.

• Anthropic user profiles scope safety enforcement to one end customer.
• GitHub CLI expiring tokens shrink the damage window when an agent's token leaks.
• The Claude SDK credential changes fix one credential per client and set a clear lookup order.

NVIDIA added a hardware angle on October 21. Its OpenShell Reference Architecture is an open-source secure runtime for agents. A BlueField-4 component called "Sentry" watches agents out-of-band and enforces policy in silicon. Partners include Anthropic, OpenAI, Google, Meta, Okta, 1Password and CrowdStrike. The announcement does not mention MCP and does not name a license, so the open-source claim needs a closer look once the code appears.

The standards track continues in parallel. The IETF draft draft-ietf-wimse-aims-00 on AI agent authentication was published September 15. Expect it to come up at the events ahead.

Personal Agent Protocol Still in Draft

The Personal Agent Protocol, nicknamed "Poppy," remains a draft. Its sample discovery file shows protocol_version "0.2" under Apache 2.0. Agents discover each other through /.well-known/poppy.json, sign in with OAuth and keep JWT sessions. Nothing changed in the window. One single-source report says the project missed its October targets.

AGNTCon + MCPCon This Week

AGNTCon and MCPCon North America run October 22-23 in San Jose. With a new MCP working group, a final Skills spec and thin adoption data on the table, expect protocol announcements there. We will cover them next week.

Infrastructure: NVIDIA Says Capacity Is the Constraint

The infrastructure story this week was supply, not speed. NVIDIA used GTC Berlin to talk about substrates, interposers and test capacity. Two of the biggest chip suppliers reported quarters that show demand still outrunning supply.

NVIDIA GTC Berlin: The Supply Chain Keynote (October 21)

Jensen Huang summed up the keynote in four words: "Capacity is the constraint." NVIDIA then laid out a supply chain expansion across packaging, testing and optics.

• Substrates: package substrate capacity rises 2.5x over three years. IBIDEN gets a multibillion-dollar advance to triple capacity at its Ono plant, ramping in Q1 2028.
• Interposers: Amkor targets more than 300% more interposer wafer capacity by the end of 2028.
• Testing: test capacity doubles from 2026 to 2027. KYEC gets a $1.1 billion advance for US test sites, with volume production starting April 2027.
• Optics: SPIL's co-packaged optics capacity rises 15x by mid-2027.

NVIDIA is now paying suppliers in advance to build plants. That tells you the bottleneck has moved past GPU design and wafer supply. It now sits in packaging, testing and optics. GPU supply will stay tight through at least 2027, and teams planning large AI clusters should plan for long lead times.

DSX POD: AI Factories in a Container

NVIDIA also introduced the DSX POD, a containerized Vera Rubin AI factory design. NVIDIA says deployment at a prepared site drops from six months to as little as 14 days. Deliveries start in early 2027. NVIDIA gave no GPU count or megawatt figure per POD.

A second announcement covered power. All of these figures are vendor-reported:

• MaxLPS cuts power by up to 30% for the same output. At Nscale, it delivered 49% more throughput inside a 264 kW budget.
• DSX Flex cuts power by up to 40% during simulated grid events. Data centers can now shed load when the grid is under stress.
• Vera Rubin runs on 45°C coolant. Warmer coolant means less chilling and lower cooling bills.
• DSX OS is open source.

Power is now the hard limit for many AI sites. Grid-aware load shedding helps data centers win interconnect approvals faster. Watch for utilities to start asking for it.

On October 16, RTX Spark PCs went on sale. Paired with Nemotron Bolt's 24GB footprint, NVIDIA is pushing hard on local agent inference.

TSMC Q3: Advanced Nodes Hit 79% (October 15)

TSMC reported third-quarter results on October 15. Revenue reached US$46.72 billion, up 41.2% year over year. Net income hit NT$763.06 billion, up 68.7%. Gross margin came in at 66.4%.

The node mix shows how fast AI chips move to new processes:

• 2nm: 8% of wafer revenue
• 3nm: 33%
• Advanced nodes overall (7nm and below): 79%

TSMC guided fourth-quarter revenue to $52.3-54.3 billion. Secondary coverage puts high-performance computing at 68% of revenue. TSMC's own release does not confirm that figure or any capex update.

ASML Q3: Customers Ordering for 2029 (October 14)

ASML reported third-quarter results on October 14. Sales hit €11.66 billion with a 57.5% gross margin and €4.96 billion in net income. ASML guided Q4 to €14.2-15.2 billion and full-year 2026 to €44-45 billion.

The detail that matters is the order horizon. Some customers want to place orders for 2029 and 2030. ASML says its supply for 2027 and 2028 will not fully meet demand. ASML did not disclose a bookings figure. When the company that makes the lithography machines is sold out two years ahead, every chip downstream stays scarce.

Anthropic and Nscale: A Second Deal in Talks (Unconfirmed)

Bloomberg HT, citing Bloomberg, reported on October 19 that Anthropic is in talks with Nscale for a second deal of roughly $45 billion. We did not see the original Bloomberg story, so this rests on secondary write-ups. The reported deal covers about 460 MW at Nscale's Monarch campus in West Virginia, running Vera Rubin chips. Anthropic also gets a reported right of first refusal on a third building.

The talks are not final. Both companies declined to comment. Treat this as a report, not a done deal.

What We Did Not See

We found nothing dated in the window on HBM memory, Google TPUs, AWS Trainium or new gigawatt-scale power deals. The Open Compute Project Summit announcements landed on October 12, just before this window. Those included Meta adopting NVIDIA Spectrum-6, AMD's Helion rack and Microsoft's Maia 300 chip.

The Data Layer Takeaway

Three threads from this week point at the data layer.

First, agents are getting cheaper to run and easier to host. At $0.15 per million input tokens, an agent can read a lot of table metadata before the bill matters. Open models with 1M context make private deployment practical. The limit is no longer the model. It is whether the agent can find governed, well-described data.

Second, credentials and approvals got stricter everywhere. Expiring tokens, per-customer safety profiles and human-only approval checks all point the same way. Agents will act on your data, and every action needs an owner and an audit trail. A lakehouse with a governed catalog and fine-grained access control gives agents that boundary.

Third, MCP is reorganizing around tasks and events. Data work is long-running by nature. The protocol that lets an agent start a job, track it and hear when it finishes will shape how agents interact with query engines and catalogs.

What to Watch Next Week

• October 22-23: AGNTCon + MCPCon North America in San Jose
• October 23: MiniMax M3.1 Flash weights (reported) and Nemotron 3.5 Bolt E4B
• October 28-29: GitHub Universe
• October 31: DeepSeek Search and Fetch billing starts for harness users, and the deadline for Mistral Large 4 weights
• November 16: Copilot retires Opus 4.8, Opus 5 and GPT-5.6 Terra
• November 30: Claude Sonnet 4.5 retires, and Gemini 4 Argon introductory pricing ends

Resources to Go Further

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