DEV Community: Tran Tien Van

Gemini 3.8 Flash TTS: Price, Rankings and the Fine Print

Tran Tien Van — Fri, 25 Sep 2026 04:11:52 +0000

Gemini 3.8 Flash TTS and Flash-Lite TTS bring prompt-based voice design at low prices. Here's what they cost, how they rank independently, and the catches.

Key takeaways

Google released Gemini 3.8 Flash TTS and Flash-Lite TTS on September 23, 2026, in the Gemini API and Google AI Studio.
Flash TTS costs about $0.81 per hour of audio and Flash-Lite about $0.54, until prices double on January 1, 2027.
On Artificial Analysis's independent Speech Arena, Flash TTS ranks second and Flash-Lite sixth, at a third of the price of several rivals.
For cloned voices, they rank mid-pack, behind Inworld, Cartesia and ElevenLabs.
Google's claim of first place comes from Hume AI, which licenses technology to Google. Its founder now works at Google DeepMind.

📖 Read the full guide on Van Data Team → Gemini 3.8 Flash TTS: Price, Rankings and the Fine Print

GDPval-AA Chart Fact-Check: Opus 5.5 vs GPT-6 Astra on Cost

Tran Tien Van — Thu, 24 Sep 2026 10:48:21 +0000

A viral GDPval-AA chart says Opus 5.5 crushes GPT-6 Astra at a tenth of the cost. We check every claim, fix the numbers, and show the fairer comparison.

Key takeaways

On Artificial Analysis's GDPval-AA test, Claude Opus 5.5 scores 1846 Elo at max effort. GPT-6 Astra scores 1542 at max.
The viral post's main point holds: on Anthropic's chart, Opus 5.5 is higher than Astra at every cost level where both appear.
But Opus 5.5 at medium beats Astra at max by just 34 points, at about a fifth of the cost. The post says a tenth.
The post's Terminal-Bench figures come from Anthropic's own chart, not Artificial Analysis. Independently, the two models are close to tied there.
At matched cost, the GDPval-AA gap is 210 to 280 points, a stronger finding than the one the post chose.

📖 Read the full guide on Van Data Team → GDPval-AA Chart Fact-Check: Opus 5.5 vs GPT-6 Astra on Cost

GPT-6 Sol vs Claude Opus 5.5, Plus Luna: Best Value per Task

Tran Tien Van — Wed, 23 Sep 2026 17:18:44 +0000

GPT-6 Sol vs Claude Opus 5.5, plus Luna, at matched budgets: who scores higher per dollar, a hands-on coding test, speed, and how to route between them.

Key takeaways

On the independent Artificial Analysis index, Claude Opus 5.5 scores 58 at its top setting, GPT-6 Sol 48 and GPT-6 Luna 37.
Per token, Sol costs half as much as Opus 5.5, and Luna costs a fortieth as much.
At matched cost, Sol wins up to a score of about 44. Above 48, only Opus 5.5 gets there.
In one hands-on coding test at the high setting, Sol cost $0.26 and scored higher on quality than Opus 5.5 at $0.87.
Anthropic's model at Sol's price, Claude Sonnet 5, scores far lower per dollar. A three-model routing plan beats any single choice.

📖 Read the full guide on Van Data Team → GPT-6 Sol vs Claude Opus 5.5, Plus Luna: Best Value per Task

GPT-6 Sol and Luna: Half the Price, and Where Each One Fits

Tran Tien Van — Wed, 23 Sep 2026 15:58:33 +0000

GPT-6 Sol and Luna cut GPT-5.6 prices in half. Here's what independent tests show, where each model fits, and how they compare with Opus 5.5 and Astra.

Key takeaways

OpenAI released GPT-6 Sol and GPT-6 Luna on September 22, 2026, at half the list price of GPT-5.6 Sol and Luna.
GPT-6 Sol costs $2 input and $10 output per million tokens. GPT-6 Luna costs $0.10 and $0.50.
On independent tests, Sol costs about 47% less per task than GPT-5.6 Sol and runs about 55% faster, but scores just 1 point higher.
Luna scores the same as GPT-5.6 Luna for less than half the cost per task, at about 154 tokens per second.
Both have weak spots. Sol slipped on one knowledge-work test, and Luna scores near zero on a factual-recall test that penalizes wrong answers.

📖 Read the full guide on Van Data Team → GPT-6 Sol and Luna: Half the Price, and Where Each One Fits

Claude Opus 5.5 Benchmarks: What the Chart Shows and Hides

Tran Tien Van — Wed, 23 Sep 2026 02:59:25 +0000

Claude Opus 5.5 benchmarks vs Fable 5.1, Opus 5, GPT-6 Astra and GPT-5.6 Sol, row by row, with the footnotes explained and independent results side by side.

Key takeaways

Anthropic's chart shows Claude Opus 5.5 leading seven of nine rows. GPT-6 Astra leads on business workflows and agentic science research.
In the six rows with an Astra number, Opus 5.5 leads four. Three rows have no Astra number, and two have no OpenAI number at all.
Several leads are within noise, including FrontierCode by 1.1 points and Chartography by 0.6.
On Terminal-Bench 4.0, Anthropic's chart shows an 8.5-point lead over Astra. Artificial Analysis's own run shows 1 point.
Independently, Opus 5.5 scores 58 on the Artificial Analysis index, against 53 for Fable 5.1 and Astra, 51 for Opus 5 and 47 for GPT-5.6 Sol.

📖 Read the full guide on Van Data Team → Claude Opus 5.5 Benchmarks: What the Chart Shows and Hides

Grok 4.7 vs Fable 5.1 vs GPT-6 Astra: Real Cost per Task

Tran Tien Van — Tue, 22 Sep 2026 17:19:13 +0000

Grok 4.7 vs Fable 5.1 vs GPT-6 Astra on independent tests: who scores highest, who's cheapest per task, and which to use for coding, research and agents.

Key takeaways

On the independent Artificial Analysis Intelligence Index, Fable 5.1 and GPT-6 Astra tie at 53 at their top settings. Grok 4.7 scores 46.
Grok 4.7 lists at $2 input and $6 output per million tokens. Fable 5.1 and GPT-6 Astra both list at $10 and $50.
Per task, the picture flips. At the high setting, Astra costs $1.73 per task, Grok 4.7 $2.73 and Fable 5.1 $3.91.
Fable 5.1 leads knowledge-work tasks, long context and hard questions. Astra leads terminal work, automation and research physics. Grok 4.7 wins none of the ten tests outright.
Grok 4.7 still makes sense for input-heavy, low-reasoning work, where its low per-token price does carry through.

📖 Read the full guide on Van Data Team → Grok 4.7 vs Fable 5.1 vs GPT-6 Astra: Real Cost per Task

Claude Opus 5.5: Tops the Independent Index at a Lower Price

Tran Tien Van — Tue, 22 Sep 2026 17:15:04 +0000

Claude Opus 5.5 leads the Artificial Analysis index and costs less than Opus 5. Here's what independent tests show, what it costs per task, and the caveats.

Key takeaways

Anthropic released Claude Opus 5.5 on September 22, 2026, at $4 input and $20 output per million tokens, down from $5 and $25 for Opus 5.
On the independent Artificial Analysis Intelligence Index, it scores 58 at its top setting, ahead of Fable 5.1 and GPT-6 Astra at 53.
At the high setting, it scored 54 for $1.82 per task. That's more than Astra's best score, at a little over half of Astra's top-setting cost.
At its top setting, it's very verbose, at about 119,000 output tokens per task. That makes it cost more per task than Astra there.
Most cybersecurity tasks are routed to an older model, advanced biology work needs approval, and thinking can't be turned off.

📖 Read the full guide on Van Data Team → Claude Opus 5.5: Tops the Independent Index at a Lower Price

Grok 4.7: Same Price as Grok 4.6, but Check Cost per Task

Tran Tien Van — Mon, 21 Sep 2026 17:14:23 +0000

Grok 4.7 keeps Grok 4.6's $2/$6 pricing and posts better scores. Here's what improved, what independent tests show, and why cost per task still needs a check.

Key takeaways

xAI released Grok 4.7 on September 21, 2026, with the same per-token prices as Grok 4.6 and, xAI says, the same speed.
On xAI's own tests, the biggest jump is Terminal-Bench 4.0, from 20.3% to 38.0%. CursorBench 4.0 rose from 40.4% to 46.3%.
On the independent Artificial Analysis Intelligence Index, Grok 4.7 scores 46 against 44 for Grok 4.6, a real but smaller gain.
At its highest setting, Grok 4.7 used 240 million tokens on that index, against 94 million for Grok 4.6 at high. Check cost per task, not just price per token.
For most teams, the right move is a quick side-by-side test at the default high setting, with Grok 4.6 kept as a fallback.

📖 Read the full guide on Van Data Team → Grok 4.7: Same Price as Grok 4.6, but Check Cost per Task

Experiential Marketing in the AI Era: Make Events Citable

Tran Tien Van — Mon, 21 Sep 2026 04:17:03 +0000

Experiential marketing is growing as AI floods feeds with content. But most event buzz never reaches AI search. Here's how to make your experiences citable.

Key takeaways

Experiential marketing spend passed its pre-pandemic peak, reaching $128.35 billion globally in 2024, according to PQ Media.
In EventTrack 2026, 84% of consumer event marketers and 86% of B2B marketers plan to spend more on events this year.
61% of consumers say they're more inclined to buy after a live experience, and 59% feel more positive about the brand, per EventTrack.
AI engines mostly cite Reddit, YouTube, LinkedIn, review sites and editorial pages. Attendees mostly post to Facebook and Instagram, or talk in private.
Close that gap on purpose: publish a recap page, send content to platforms AI reads, and track AI visibility alongside leads.

📖 Read the full guide on Van Data Team → Experiential Marketing in the AI Era: Make Events Citable

AI Slowdown Lawsuit: Is Safety Coordination Collusion?

Tran Tien Van — Mon, 21 Sep 2026 03:32:44 +0000

An AI slowdown lawsuit says Anthropic, OpenAI, SpaceXAI and Google broke antitrust law by agreeing to slow down. Here's the claim, the defenses and what's next.

Key takeaways

Four paid subscribers sued Anthropic, OpenAI, SpaceXAI and Google in federal court in San Francisco on September 18, 2026.
They say that publicly backing a joint slowdown was a deal among rivals to cut output, which US antitrust law forbids.
The key evidence is timing: Dario Amodei's September 12 essay calling for coordination, and same-day agreement from Sam Altman, Elon Musk and Demis Hassabis.
The big questions: do public statements prove a deal, has anyone been harmed yet, and how much does safety count?
Nothing changes for API users today. But the case could make labs wary of working on safety together in public.

📖 Read the full guide on Van Data Team → AI Slowdown Lawsuit: Is Safety Coordination Collusion?

Jev API Getting Started: What the Free $5 Credit Buys

Tran Tien Van — Mon, 21 Sep 2026 02:38:23 +0000

Jev is now open to everyone with a $5 free credit. Here's how to make your first Jev API call, what the credit really buys, and what to test first with it.

Key takeaways

Jev is open to all users with no waitlist, a week after TypeSafe AI launched it in early access.
New users get a $5 credit. At $0.042 per million input tokens, with output free, that's about 119 million input tokens.
In practice, that's roughly 400,000 short calls, or about 85,000 calls on ticket-sized inputs.
Your first Jev API call takes one package, one API key, and a few lines of Python.
Spend the credit on a labeled test of your own decisions, not on demos. That's what tells you if Jev fits.

📖 Read the full guide on Van Data Team → Jev API Getting Started: What the Free $5 Credit Buys

Jev vs Fable 5.1 vs GPT-6 Astra: Which Model for Which Job

Tran Tien Van — Sat, 19 Sep 2026 16:14:44 +0000

Jev vs Fable 5.1 vs GPT-6 Astra isn't a normal model race: one classifies, two reason. Here's how they compare on cost, speed, accuracy, and best use.

Key takeaways

Jev is a classifier: it answers structured questions with probabilities and can't write text. Fable 5.1 and GPT-6 Astra are frontier models that can.
Jev lists input at $0.042 per million tokens with output free. Fable 5.1 and GPT-6 Astra both list at $10 input and $50 output per million.
In 6,003 independent rubric checks, Jev matched Fable 5.1's verdict 91.5% of the time at $160 against $33,000 per million answers.
Between the two frontier models, Fable 5.1 leads the independent Intelligence Index 66 to 61, while GPT-6 Astra leads most rows of OpenAI's own table.
The best setup often uses Jev for fast decisions and Fable 5.1 or GPT-6 Astra for reasoning, in the same agent.

📖 Read the full guide on Van Data Team → Jev vs Fable 5.1 vs GPT-6 Astra: Which Model for Which Job