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Model comparison

Gemini 3.1 Pro vs MiniMax M3

Google against MiniMax, compared on context, price, and verified benchmark results.

Catalog record checked September 5, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Google

Gemini 3.1 Pro

Frontier

vs

MiniMax

MiniMax M3

Frontier · Open weights

AI model capability comparison
SpecificationGemini 3.1 ProMiniMax M3
ProviderGoogleMiniMax
TierFrontierFrontier
Context windowWinner: 1.05M1M
Max output66KNot verifiedUnverified
Input / 1M tokens$2Winner: $0.30
Output / 1M tokens$12Winner: $1.20
WeightsClosedOpen
ParametersNot disclosedUnverified428B total / 23B active (MoE)
Reasoning levelslow, medium, highlow, high, max
Modalitiestext, image, video, audio, pdftext, image, video
API model idgemini-3.1-pro-previewminimax-m3
ReleasedFebruary 19, 2026June 1, 2026
Artificial Analysis Intelligence Index (2026-08-14)Winner: 6051
SWE-bench Verified (2026-02)80.6Not verifiedUnverified
GPQA Diamond (2026-02)94.3Not verifiedUnverified
Humanity's Last Exam (2026-02)44.4Not verifiedUnverified
Terminal-Bench 2.1 (2026-07)Winner: 73.866

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

  • 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
  • 2026-07: Google DeepMind model evaluation report (vendor, Terminus-2; own Feb report separately reported TB 2.0 = 68.5 — versions preserved)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
  • 2026-06-01: MiniMax blog (vendor, Terminus 2 scaffolding, 2h timeout)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
  • 2026-02: Google DeepMind model evaluation report (vendor, no tools; 51.4 with search+code)Real GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.

Pricing tiers: Gemini 3.1 Pro: $2/$12 per MTok (≤200K); $4/$18 (>200K). Still 'Preview' as of 2026-08-29; 3.5 Pro not yet released. · MiniMax M3: $0.30/$1.20 per MTok; open (community license). 428B/23B active MoE, native multimodal. Rate is the ≤512K-prompt tier; higher above.

FrontierRecord checked September 5, 2026

Gemini 3.1 Pro

Gemini 3.1 Pro is Google's current flagship Pro model with record benchmark scores and a 1M-token context.

Best for

  • Very long documents
  • Multimodal reasoning
  • Frontier knowledge work

Watch out

Still in Preview; 3.5 Pro is 'coming soon' but unreleased as of 2026-08-29.

FrontierOpen weightsRecord checked September 5, 2026

MiniMax M3

MiniMax M3 is an open-weight (community license) 428B MoE with native multimodal and 1M context.

Best for

  • Open-weight deployments
  • Multimodal
  • Long-context

Watch out

Community license, not fully open; verify terms.

When the cheaper one wins

MiniMax M3 is cheaper on output at $1.20 per million tokens against $12 for Gemini 3.1 Pro — about 10×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

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Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 3/5 core specs verified on both sides — Not published for at least one side: max output, parameter count.
  • 2 shared named benchmarks with differing scores — Measured on: Artificial Analysis Intelligence Index, Terminal-Bench 2.1.
  • Verified within the last 90 days — Newest catalog check was 6 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? Gemini 3.1 Pro · MiniMax M3

Common questions

Gemini 3.1 Pro vs MiniMax M3

Answered from the verified figures on this page rather than general guidance.

Is Gemini 3.1 Pro or MiniMax M3 cheaper for input?

MiniMax M3 is cheaper at $0.30 per million input tokens, against $2 for Gemini 3.1 Pro — roughly 6.7× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 3.1 Pro has tiered pricing: $2/$12 per MTok (≤200K); $4/$18 (>200K). Still 'Preview' as of 2026-08-29; 3.5 Pro not yet released. MiniMax M3 has tiered pricing: $0.30/$1.20 per MTok; open (community license). 428B/23B active MoE, native multimodal. Rate is the ≤512K-prompt tier; higher above.

Is Gemini 3.1 Pro or MiniMax M3 cheaper for output?

MiniMax M3 is cheaper at $1.20 per million output tokens, against $12 for Gemini 3.1 Pro — roughly 10× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 3.1 Pro has tiered pricing: $2/$12 per MTok (≤200K); $4/$18 (>200K). Still 'Preview' as of 2026-08-29; 3.5 Pro not yet released. MiniMax M3 has tiered pricing: $0.30/$1.20 per MTok; open (community license). 428B/23B active MoE, native multimodal. Rate is the ≤512K-prompt tier; higher above.

Which has the larger context window, Gemini 3.1 Pro or MiniMax M3?

Gemini 3.1 Pro accepts 1.05M tokens against 1M for MiniMax M3. This only matters if you routinely send very long documents or large codebases.

Do Gemini 3.1 Pro and MiniMax M3 support the same reasoning levels?

Gemini 3.1 Pro exposes low, medium, high, while MiniMax M3 exposes low, high, max.

Should I use Gemini 3.1 Pro or MiniMax M3?

Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. Gemini 3.1 Pro suits very long documents; MiniMax M3 suits open-weight deployments.

Can I self-host Gemini 3.1 Pro or MiniMax M3?

MiniMax M3 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Gemini 3.1 Pro is a closed model whose supported access paths are controlled by its provider.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Input price: MiniMax M3 costs $0.30 per 1M tokens versus $2 for Gemini 3.1 Pro — a 6.7x difference at the headline tier.
  • Context: Gemini 3.1 Pro takes 1.05M against 1M for MiniMax M3 — only decisive if your prompts approach the smaller window.
  • Measured capability: Gemini 3.1 Pro leads Artificial Analysis Intelligence Index 60 to 51 (measured 2026-08-14).
  • Deployment: MiniMax M3 publishes weights you can self-host; the other is API-only.
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