MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
中文
Model Comparison · Head to Head

GPT-6 Astra vs Gemini 3.1 Pro

GPT-6 Astra wins on Overall, Coding; Gemini 3.1 Pro wins on Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorOpenAI / Google
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose GPT-6 Astra when coding depth, long-context reliability matter most; choose Gemini 3.1 Pro when lower cost, lower latency, fine-tuning/ecosystem is the priority.

Choose GPT-6 Astra if you…

  • Best-in-class computer use
  • Frontier research & reasoning
  • Autonomous long-horizon tasks
  • Strongest cybersecurity (gated)
  • Best for: Computer use, Deep research, Cybersecurity

Choose Gemini 3.1 Pro if you…

  • Native audio and video
  • Strong scientific computing
  • Largest 2M context
  • Search integration
  • Best for: Multimodal, Scientific reasoning, Audio & video
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 26 tracked models.

GPT-6 Astra Higher overall
OpenAI · #1 overall
Overall96
Coding97
Multimodal90
VS
Gemini 3.1 Pro
Google · #5 overall
Overall83
Coding74
Multimodal92

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionGPT-6 AstraGemini 3.1 ProVerdict
VendorOpenAI (US)Google (US)Different vendors
Released2026.092026.05GPT-6 Astra is newer
Overall (rank)96 · #183 · #5GPT-6 Astra +13
Coding97 · #374 · #12GPT-6 Astra +23
Multimodal90 · #792 · #3Gemini 3.1 Pro +2
Context window1.05M2MGemini 3.1 Pro larger
Max output128K128KTie
Effective-context9692GPT-6 Astra more reliable
Input $/1M$10$2Gemini 3.1 Pro cheaper
Output $/1M$50$12Gemini 3.1 Pro cheaper
Cache discount50% offnoneGPT-6 Astra deeper
Speed~35 tok/s~60 tok/sGemini 3.1 Pro faster
TTFT1.1s0.7sGemini 3.1 Pro snappier
Function calling9478GPT-6 Astra ahead
Refusal rate~13%~12%Gemini 3.1 Pro less restrictive
English9990GPT-6 Astra
Chinese7275Gemini 3.1 Pro
Modalitiestext, imagetext, image, audio, videodifferent coverage
Open weightsNoNoBoth closed
Fine-tuningNoYes
Free tierNo free API tier; Fast mode delivers up to ~2x throughputGemini App free with limited quota; API free tier available
SOC2 / no-trainyes / yesyes / yes
Private deploymentNoNoNeither

Fields drawn from vendor public documentation and the Modelspectra 26-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

GPT-6 Astra leads the overall aggregate by 13 points (96 vs 83). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Gemini 3.1 Pro remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a decisive gap: GPT-6 Astra scores 97 against 74. On multi-file edits, SWE-style tickets and long-horizon agent loops GPT-6 Astra needs fewer correction turns; Gemini 3.1 Pro is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

Gemini 3.1 Pro leads multimodal 92 vs 90. A concrete modality difference: Gemini 3.1 Pro additionally handles audio, video.

Speed & latency

Gemini 3.1 Pro is faster in interactive use: ~60 tok/s with 0.7s TTFT versus ~35 tok/s with 1.1s TTFT (about 1.7× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1.05M for GPT-6 Astra and 2M for Gemini 3.1 Pro. Crucially, the larger nominal window does not win on usable recall: Gemini 3.1 Pro advertises 2M but GPT-6 Astra scores higher on effective-context (96 vs 92), i.e. it actually retains more of what it was given.

Price & total cost

Gemini 3.1 Pro is the cheaper API at $2/$12 versus GPT-6 Astra at $10/$50 per 1M input/output tokens — list input is about 5.0× lower. Cache discounts (GPT-6 Astra 50%) shift the effective bill, worked out below.

Chinese vs English

English: GPT-6 Astra 99 vs Gemini 3.1 Pro 90. Chinese: 72 vs 75. Both are US-based models; for Chinese-first workloads also compare domestic models on the leaderboard.

Tool use & ecosystem

Function-calling score: GPT-6 Astra 94 vs Gemini 3.1 Pro 78, so GPT-6 Astra has the edge on structured tool use. Fine-tuning is available from Gemini 3.1 Pro. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthGPT-6 AstraGemini 3.1 ProGap
List priceno cache applied$2,500100M in × $10  +  30M out × $50$560100M in × $2  +  30M out × $124.46×gap
With caching90% of inputs cache-hit$2,05090M cached in × $5  +  10M in × $10  +  30M out × $50$560no published cache discount3.66×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose GPT-6 Astra (coding 97 vs 74).
IF you serve real-time users and latency is a product KPI  →  choose Gemini 3.1 Pro (~60 tok/s, 0.7s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose Gemini 3.1 Pro ($$2/$$12 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose GPT-6 Astra (effective context 96 vs 92).
07

Frequently asked questions

Is GPT-6 Astra worth the higher price over Gemini 3.1 Pro?
At list the input rate is 5.0x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when GPT-6 Astra's stronger dimensions protect revenue; for routine volume Gemini 3.1 Pro is the economical pick.
Which is better for agentic coding?
GPT-6 Astra is decisively stronger for coding (97 vs 74 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; Gemini 3.1 Pro is fine for routine scripts.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, GPT-6 Astra is about $2,050/month and Gemini 3.1 Pro about $560/month after cache discounts ($2,500 and $560 at list).
Does the bigger context window actually matter?
Nominal windows are GPT-6 Astra (1.05M) and Gemini 3.1 Pro (2M), but usable recall follows the effective-context score (96 vs 92). Prefer the higher effective-context model for long-document work where nothing can be missed.
Which one supports fine-tuning?
Gemini 3.1 Pro supports fine-tuning; GPT-6 Astra does not at this tier. If you plan to adapt the model to a narrow domain, that is a concrete differentiator.
Which handles multimodal inputs better?
Multimodal scores are 90 (GPT-6 Astra) vs 92 (Gemini 3.1 Pro), with modality coverage text/image versus text/image/audio/video. Match the model to the input types your product actually receives.