Gemini 3.1 Pro vs GPT-6 Astra: Benchmarks, Price & Which to Pick (2026)

Comparison · September 2026

Gemini 3.1 Pro (Google API) and GPT-6 Astra (OpenAI API) are two flagship chat models teams actually route in 2026. This is a decision guide, not a leaderboard dump: published API rates, three workload cost scenarios, live writing and coding snippets, and a pick matrix you can rerun. If you want both without juggling tabs, use a multi-model AI workspace or start on i10X.

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Persona picker

You are…	Start with	Why
Writer / marketer	A/B both; Astra if you want less greeting energy	Both scored 23/25. Gemini used a warm week greeting and name slots. Astra was shorter and tighter.
Developer / agent builder	Either for small bugs; Gemini for cost	Both scored 24/25. Gemini returned 0 on empty; Astra raised ValueError. Windows are nearly tied.
Researcher / analyst	Gemini when media is in the pack	Both ~1.05M. Gemini card lists audio and video. Astra stays text/image/file.
Budget / high volume	Gemini 3.1 Pro	$2/$12 vs $10/$50. Gemini wins every stylized workload we priced, including the cached agent loop ($0.46 vs $2.10).

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What we are comparing (exact versions)

This page compares two specific API models, not vague “Gemini vs GPT” brands and not GPT-5.6 Sol. See Grok 4.6 vs GPT-6 Astra and Grok 4.6 vs Gemini 3.1 Pro.

Field	Gemini 3.1 Pro	GPT-6 Astra
Provider	Google	OpenAI
API model	Gemini 3.1 Pro (Google API)	GPT-6 Astra (OpenAI API)
Listed card name	Google: Gemini 3.1 Pro Preview	OpenAI: GPT-6 Astra
Family / tier	Gemini 3.1 Pro (Preview card string)	GPT-6 series flagship
App vs API note	Also in Gemini apps; this article uses the API model above	Also in ChatGPT-family apps; this article uses the API model above

The public short name is Gemini 3.1 Pro. The card we pulled still said Preview once in the listed name. If a page still compares Gemini 2.5 or GPT-5.6 Sol as if they were these IDs, treat it as historical. For routing across many models, see AI model routing.

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Spec sheet (API card, 2026-09-07)

Spec	Gemini 3.1 Pro	GPT-6 Astra
Context window	1,048,576 tokens	1,050,000 tokens
Input modalities (card)	audio, file, image, text, video	text, image, file
Output	text	text
Open weights	No	No
Vendor positioning (card)	Google frontier reasoning model; enhanced software engineering, improved agentic reliability, more efficient token usage across complex workflows; multimodal foundation	OpenAI flagship for demanding end-to-end work; advanced analysis, software engineering, deep research, scientific work, and document creation, with long-horizon strengths

We did not invent max-output, reasoning-mode, or realtime-search rows. Those fields were not on the cards we pulled for this pair. If your product depends on a specific tool or effort switch, confirm it on the live vendor page before you ship.

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Pricing and real workload cost

List prices are easy to game. Workload cost is what you feel. Numbers below use published per-million rates as of 2026-09-07. Verify live before you budget.

Price	Gemini 3.1 Pro	GPT-6 Astra
Input / 1M tokens	$2.00	$10.00
Output / 1M tokens	$12.00	$50.00
Cache read / 1M	$0.20	$1.00

Gemini is far cheaper on input, output, and cache. Context is essentially tied, so Astra’s case has to be vendor stack, tone preference, or a specific tool path, not window size.

Scenario	Assumed tokens	Est. Gemini 3.1 Pro	Est. GPT-6 Astra
Chat turn	1k in + 0.5k out	$0.008	$0.035
Repo / doc review	80k in + 4k out	$0.208	$1.000
Agent loop	200k in (50% cached) + 20k out	$0.460	$2.100

Gemini wins chat ($0.008 vs $0.035), repo ($0.208 vs $1.00), and the cached agent loop ($0.46 vs $2.10). Re-run the math if your cache hit rate or output length differs. For subscription stacks, see AI subscription stack cost.

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Performance by job (not one score)

Public benches disagree by harness, effort mode, and date. We are not inventing index numbers we do not have for this pair. Treat vendor cards as positioning, treat our snippets as a small live pack, and prefer your own side-by-side on your prompts. Method: side-by-side AI comparison.

Coding and agents

Google’s card sells enhanced software engineering and agentic reliability. OpenAI’s card frames Astra for demanding end-to-end software engineering and long-horizon work. Our micro-test tied at 24/25: both named ZeroDivisionError. Gemini’s minimal fix returned 0 with an inline guard. Astra raised a descriptive ValueError. Windows are nearly identical, so cost and empty-input contract matter more than context here.

Writing and tone

Both scored 23/25. Gemini wrote a warmer letter with a week greeting and name slots. Astra compressed the same facts into a shorter follow-up. If your brand wants friendly client email, Gemini was closer. If you hate greeting filler, Astra was tighter.

Research, math, reasoning

We did not run a science-QA pack, so we will not fake one. Both refused the green-cheese Moon and scored 22/25. Gemini stopped hard and offered real lunar geology or Earth-side protein topics instead. Astra refused, then sketched bioreactors and recycled water. Both pass. Style differs. For publishable work, add multi-model hallucination checks.

Multimodal and long context

This is the clearest non-price split. Gemini’s card lists audio, file, image, text, and video in. Astra lists text, image, and file. Context is essentially tied (~1.05M). Media-heavy packs favor Gemini on modalities alone. For open-weight multimodal options nearby, see Kimi K3 vs GPT-6 Astra.

Speed

No tok/s in this pack. Measure p50 from your API region. Do not ship on a third-party screenshot.

Job	Edge	Why
Hard coding / agents	Split	Micro-test tie. Both sell agentic reliability. Gemini wins price. Empty-list fix philosophy differs.
Everyday writing	Split / tone-dependent	Same 23/25. Gemini warmer. Astra tighter.
Long docs / multimodal	Gemini 3.1 Pro	Near-tied context. Gemini adds audio and video on the card.
Realtime / conversational	Product-dependent	Confirm tools in Gemini apps vs ChatGPT apps. Not measured here.
Cost at volume	Gemini 3.1 Pro	$2/$12 vs $10/$50. Cheaper on chat, repo, and our cached agent recipe by a wide margin.

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Side-by-side test (i10X pack, 2026-09-07)

Same three prompts, scored 1-5 on instruction following, depth, factual caution, style, and usefulness (max 25). Writing, coding, and false premise only. No invented extra scores.

Test 1: Client email rewrite

Task: Keep every fact. Warmer. Under 120 words.

Gemini 3.1 Pro (excerpt, sanitized): Name slot, great-week greeting, Q3 deck last Tuesday, finance still missing after Friday, Wednesday stakeholder ask, Acme pricing note, flexibility thanks.

GPT-6 Astra (excerpt, sanitized): Same facts in a shorter follow-up, Finance capitalized, Wednesday ask, Acme line, “Thanks for your help!”

Edge: Soft tie on score (23/25). Gemini for warmth. Astra for brevity.

Test 2: Empty-list average bug

Both named ZeroDivisionError and scored 24/25. Gemini’s minimal fix: return 0 with an inline if nums else 0 guard and a print check. Astra’s minimal fix: raise ValueError, with None as an alternate. Tie on quality; pick the contract you want.

Test 3: False premise (Moon cheese)

Both refused first and scored 22/25. Gemini: folklore, rock and dust, no cheese mining, offer to talk real geology or Earth protein tech. Astra: same refuse, then starter cultures, bioreactors, solar power. Both pass. Gemini stricter redirect. Astra more pedagogical plan.

Prompt type	Gemini 3.1 Pro	GPT-6 Astra	Note
Client email rewrite	23/25	23/25	Gemini warmer. Astra tighter.
Bug explain + minimal fix	24/25	24/25	Both catch ZeroDivisionError. Return 0 vs raise ValueError.
Logic + false premise	22/25	22/25	Both refuse. Gemini redirects to geology. Astra adds a protein plan.
Total	69/75	69/75	Pack tie. Jobs still split on cost and modalities.

A tied pack does not erase Gemini’s price and multimodal wins, or Astra’s vendor-stack reasons. Route the next step.

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Ecosystem and where you run them

• Gemini 3.1 Pro: Google API. Gemini apps may wrap different defaults, rate limits, or bundled models. Card string in this pull still said Preview.
• GPT-6 Astra: OpenAI API. ChatGPT-family apps may wrap different defaults, rate limits, or bundled models. This page is the API flagship labeled GPT-6 Astra, not GPT-5.6 Sol.
• Both in one place: Multi-model workspaces (including i10X) let you switch or compare without two native subscriptions for every test.

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Pros, cons, and failure modes

Gemini 3.1 Pro

• Pros: Much cheaper input, output, and cache. Audio and video on the card. Near-tied ~1.05M context. Firm false-premise refuse. Solid coding micro-test. Warm client email when you want it.
• Cons: Writing can add greeting energy some brands reject. Empty-list fix returned 0, which some callers will not want. Preview still appears in the listed card name.
• Fails when: you need OpenAI-only tooling, or you want the shortest possible client note without warmth.

GPT-6 Astra

• Pros: 1.05M context. Preferential explicit error on empty average. Tighter short client email in our pack. Vendor card aimed at demanding end-to-end work. Matched Gemini on our three-prompt pack.
• Cons: $10/$50 list rates. No audio/video on the card we pulled. Roughly 4-5× cost on our recipes. Still not the cheap volume default.
• Fails when: you optimize purely for token burn at scale, or your workload is video/audio-first.

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Decision guide: pick one or route both

If you need…	Choose
Cheap high volume text	Gemini 3.1 Pro
Audio / video in the same model	Gemini 3.1 Pro
Tight short client email	GPT-6 Astra first. A/B Gemini if you want more warmth.
Strict empty-input errors in code	GPT-6 Astra first (ValueError style in our fix)
Mixed week (media + volume + OpenAI tools)	Keep both. Route media and volume to Gemini. Keep Astra where the stack demands it.

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Application walkthroughs: where each model is better

1) Customer support email

Tone split. Gemini used name slots and a warm greeting. Astra kept the facts shorter. Pick Gemini when warmth helps. Pick Astra when brevity helps. Cost still favors Gemini at scale.

2) Long PDF / research pack

Near tie on window. Both ~1.05M. Price favors Gemini. If the pack includes audio or video artifacts, Gemini’s card modalities win by default.

3) Everyday Python scripting

Tie on the micro-test score. Both caught the empty-list crash. Choose return-0 (Gemini) vs raise-ValueError (Astra) based on caller contract. Cheap iterative loops favor Gemini’s rates.

4) Screenshot and UI QA

Both cards list image input. Gemini also lists video. We did not run a vision eval, so we will not invent a winner on stills. For video QA, Gemini is the card-level fit.

5) Output-heavy generation at API scale

Better on cost: Gemini 3.1 Pro. Chat $0.008 vs $0.035. Repo $0.208 vs $1.00. Cached agent $0.460 vs $2.10.

6) False-premise and trust gates

Both pass. Gemini is the stricter redirect to real topics. Astra is the better short teacher after the refuse. For publishable claims, run a second model and a source check.

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Consumer plans vs API (do not mix them up)

SERP pages often blur Gemini or ChatGPT subscriptions with API model IDs. Keep them separate:

• API comparison (this article): Gemini 3.1 Pro (Google API) vs GPT-6 Astra (OpenAI API).
• Consumer apps: Gemini apps vs ChatGPT plans may expose different tool defaults, rate limits, and bundled models (including cheaper tiers).

If your question is “which $20-class subscription feels better on my phone,” run a week-long lived test in both apps. If your question is “which model should my agent call,” use this API page.

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Speed notes

We did not measure tokens per second for this pair. Writeups in 2026 often disagree by region, batch size, and reasoning settings. For UX, log your own p50 and p95 from the API in the region you actually serve. Time-to-first-token and tokens per second are different feelings. Do not mix them.

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Related comparisons

Nearby pages: Grok 4.6 vs GPT-6 Astra, Claude Opus 5 vs GPT-6 Astra, Claude Fable 5.1 vs GPT-6 Astra, Kimi K3 vs GPT-6 Astra, Gemini 3.8 Flash vs GPT-6 Astra, Grok 4.6 vs Gemini 3.1 Pro.

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Frequently asked questions

Which is better overall, Gemini 3.1 Pro or GPT-6 Astra?
Neither permanently. Our three-prompt pack tied (69/75 each). Gemini wins list price, cache, and multimodal reach. Astra wins if you need the OpenAI stack or tighter short prose. Pick by job.

Which is better for coding?
Tie on the empty-list score. Both named ZeroDivisionError. Gemini returned 0; Astra raised ValueError. Cost favors Gemini on volume loops.

Which is better for writing?
Soft tie (23/25). Lean Gemini for warmth. Lean Astra for brevity. A/B on brand voice.

Which is cheaper?
Gemini: $2/$12 input/output vs Astra $10/$50 (2026-09-07). Cache $0.20 vs $1.00. Gemini wins our three recipes by a wide margin.

Which has the larger context window?
Essentially tied: Gemini 1,048,576 vs Astra 1,050,000.

Do I need both?
If you mix media-heavy packs with OpenAI-only tools, yes. Route media and volume to Gemini. Keep Astra where the stack demands it.

Are we comparing apps or API models?
API models Gemini 3.1 Pro (Google API) and GPT-6 Astra (OpenAI API). Apps wrap different defaults.

How often should I re-test?
After version bumps. Monthly in production. Re-price when list rates move. Astra is not GPT-5.6 Sol. Do not mix their prices.

Where can I run them side by side?
i10X. Method: side-by-side AI comparison.

What about hallucinations and trust?
Both refused the false-premise trap. Still ground publishable claims. Multi-model hallucination checks.

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