Grok 4.6 vs 4.5: Migrate Long-Running Agents by Accepted-Task Cost

Grok 4.6 vs 4.5: migrate long-running agents by accepted-task economics

Quick answer

SpaceXAI released grok-4.6 on August 12, 2026 as its new flagship for coding, agentic tasks, and knowledge work. It keeps Grok 4.5's 500,000-token context window and headline prices of $2 per million input tokens and $6 per million output tokens, while SpaceXAI reports stronger results on long-running agent evaluations.

Do not migrate on those headlines alone. Grok 4.6 raises cached-input pricing from $0.30 to $0.50 per million tokens below the 200K long-context threshold, and from $0.60 to $1 above it. A long coding session with a high cache-hit rate can therefore cost more even when input and output list prices look unchanged.

Run 4.5 and 4.6 on the same multi-step tasks, record context growth, retries, tool calls, human repair, and accepted results, then promote 4.6 only where the complete task economics improve. Treat API, Cursor, Grok Build, and GitHub Copilot availability as separate states.

Who this is for

This guide is for developers already routing production coding or research agents to Grok 4.5. It also helps teams evaluating Grok 4.6 through Cursor, Grok Build, or GitHub Copilot without confusing a partner announcement with verified access in every account and client.

If you are evaluating Grok for the first time, start with the Grok 4.5 coding-agent evaluation. This page focuses on the narrower migration decision: whether an existing, passing 4.5 route should move to 4.6.

What actually changed

Boundary	Grok 4.5	Grok 4.6	Migration implication
Context window	500K	500K	Capacity did not increase; measure how the agent uses it
Input / cached / output below 200K	$2 / $0.30 / $6	$2 / $0.50 / $6	Cached input is 66.7% more expensive
Input / cached / output at long-context rates	$4 / $0.60 / $12	$4 / $1 / $12	The whole request moves to the higher rate at the threshold
Modalities	Text and image to text	Text and image to text	Re-run image and structured-output contracts, not just code tasks
Agent capabilities	Function calling, structured output, reasoning	Function calling, structured output, reasoning	Tool compatibility still needs a canary
Published focus	Coding and agentic work	Longer-running agents and more ambitious interactive work	Test trajectory stability, not only first-answer quality

SpaceXAI reports that Grok 4.6 improves over 4.5 from 54% to 65.9% on DeepSWE 1.1, from 56.6% to 61.3% on FrontierCode 1.1 Extended, and from 47.1% to 57.5% on APEX-Agents. These are useful release signals, not proof for your repository: benchmark scores depend on the harness, task set, effort, and acceptance policy.

Use a paired long-running task pack

Choose six representative tasks that are long enough to expose planning and recovery behavior:

1. Fix a cross-file bug and add a regression test.
2. Migrate an API across at least five call sites without changing public behavior.
3. Complete a tool loop with one injected timeout and one recoverable invalid result.
4. Investigate a repository-wide performance issue and produce a verified patch.
5. Build a small interactive feature from a written brief and screenshot target.
6. Resume a stopped task from saved evidence without repeating completed work.

Pin the same repository commit, prompt, tools, sandbox, reasoning effort, timeout, and tool-call cap. Run at least three paired trials per task. Keep deterministic tests and screenshots outside the model so both candidates face the same acceptance gate.

Record more than tokens. A useful migration sheet includes first-pass acceptance, completed steps, repeated steps, tool failures, context size by turn, cached tokens, output tokens, wall time, and human repair minutes.

Calculate accepted-task economics

Use one cost record per trial:

model_cost = input_cost + cached_input_cost + output_and_reasoning_cost + tool_cost
recovery_cost = retry_model_cost + human_repair_minutes * internal_minute_rate
accepted_task_cost = (model_cost + recovery_cost) / accepted_tasks

Also plot prompt size by turn. Once a prompt reaches the 200K long-context threshold, SpaceXAI's pricing table applies the higher input, cached-input, and output rates to the entire request, not only the tokens above 200K. Context compaction that preserves acceptance can matter more than a small benchmark gain.

Do not mix Standard with Priority Processing during the model comparison. Priority is a separate 2x-priced service lane. First compare model versions on the same lane; test faster processing only after selecting the model.

A seven-gate migration workflow

1. Inventory every route

List direct API model IDs, moving aliases, Cursor settings, Grok Build workflows, Copilot policies, fallbacks, cached prompts, and scheduled jobs. Mark which routes can roll back independently.

2. Freeze the 4.5 baseline

Save the prompt revision, tool schema, harness version, acceptance tests, cost window, and three representative 4.5 traces. Without a fixed baseline, a simultaneous harness change can masquerade as a model improvement.

3. Prove the 4.6 API contract

Call the exact grok-4.6 model on a harmless structured-output task, a function call, an image input, and an intentional tool failure. Record the requested model, returned usage, region, status, and timestamp. Do not assume a picker label proves API behavior.

4. Run the paired pack

Alternate 4.5 and 4.6 trials to reduce time-of-day and service-load bias. Reject any comparison where effort, tool versions, timeout, or service lane differs.

5. Inspect trajectory growth

Flag repeated reads, unnecessary tool loops, premature compaction, lost constraints, and retries that rebuild context. A stronger first pass can still lose if it grows the transcript faster or requires more repair.

6. Verify partner availability separately

SpaceXAI says Grok 4.6 is available in Cursor, Grok Build, the API, and GitHub Copilot. At the time of this check, GitHub's supported-model and pricing references still listed Grok 4.5, while Cursor's changelog had not published a matching 4.6 entry. For each partner, record plan, admin policy, client version, picker visibility, successful invocation, and date. Documentation lag is an observation, not proof that a rollout failed.

7. Ramp with explicit rollback

Start with one low-risk task class, then 5%, 25%, and 100% only when acceptance, policy violations, wall time, and accepted-task cost stay within your predeclared budget. Keep 4.5 pinned as the rollback route until a representative production window passes.

Decision tree

Does 4.6 pass every safety and tool-contract canary?
  no  -> keep 4.5 and isolate the failed boundary
  yes -> does it improve accepted-task cost or a required quality gate?
           no  -> keep 4.5 for this route
           yes -> does the gain survive long-context and retry scenarios?
                    no  -> compact, narrow, or route only short tasks
                    yes -> ramp gradually with 4.5 rollback

Common mistakes

• Calling pricing unchanged while ignoring the cached-input increase.
• Comparing a 4.5 short task with a 4.6 long trajectory that crosses 200K.
• Treating SpaceXAI's benchmark chart as repository-level acceptance evidence.
• Mixing Standard and Priority lanes or changing the harness during the canary.
• Treating API success as proof of Cursor or Copilot policy, picker, and invocation.
• Removing the untrusted-repository sandbox gate because the new model self-tests more often.

Copyable decision record

date / owner / route:
baseline_model / candidate_model:
repository_commit / fixture_revision / harness_version:
reasoning_effort / service_lane / tool_versions:
first_pass_acceptance / final_acceptance:
context_by_turn / cached_input / output_and_reasoning:
retries / repeated_steps / tool_failures:
wall_time / human_repair_minutes:
accepted_task_cost_4_5 / accepted_task_cost_4_6:
partner_plan / policy / client / picker / invocation:
decision: hold | short-task-only | 5% | 25% | 100% | rollback
rollback_model / trigger:

FAQ

Is Grok 4.6 the same price as Grok 4.5?

Not exactly. Standard input and output prices match, but Grok 4.6's cached-input price is higher both below and above the 200K threshold. Calculate your actual prompt, cache, output, tool, and recovery mix.

Should every Grok 4.5 coding agent migrate?

No. Move only the task classes where paired evidence shows a required quality gain or better accepted-task economics. A stable 4.5 route can remain the better choice for short, high-cache workloads.

Is Grok 4.6 available in GitHub Copilot everywhere?

SpaceXAI announced availability on August 14 and said some Business and Enterprise organizations may need to enable the model. Because GitHub's reference pages still showed 4.5 when checked, verify the actual plan, policy, picker, client, and invocation before changing team instructions.

Sources

• SpaceXAI: Introducing Grok 4.6
• SpaceXAI model documentation: Grok 4.6
• SpaceXAI API pricing
• SpaceXAI: Grok 4.6 in GitHub Copilot
• GitHub Copilot supported models
• Cursor changelog

Comments

[Marcus Kim]

The cached-input jump from $0.30 to $0.50 matters even more when crossing 200K reprices the entire request, because a capable agent can quietly erase its quality gain through context growth. Alternating 4.5 and 4.6 trials while keeping deterministic tests and screenshots outside the model is a solid way to separate model behavior from harness noise. I'd also calculate accepted-task cost by task class rather than as one portfolio average; cross-file repairs may justify 4.6 while short, cache-heavy routes remain cheaper and steadier on 4.5.