Model comparison

Gemini 3.1 Pro vs Xiaomi MiMo-V2.5-Pro

Google against Xiaomi, 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

Xiaomi

Xiaomi MiMo-V2.5-Pro

Frontier · Open weights

AI model capability comparison
Specification	Gemini 3.1 Pro	Xiaomi MiMo-V2.5-Pro
Provider	Google	Xiaomi
Tier	Frontier	Frontier
Context window	Winner: 1.05M	1M
Max output	66K	Not verifiedUnverified
Input / 1M tokens	$2	Winner: $1
Output / 1M tokens	$12	Winner: $3
Weights	Closed	Open
Parameters	Not disclosedUnverified	1.02T total / 42B active (MoE)
Reasoning levels	low, medium, high	low, high, max
Modalities	text, image, video, audio, pdf	text, image
License	Not disclosedUnverified	MIT
API model id	gemini-3.1-pro-preview	mimo-v2-5-pro
Released	February 19, 2026	April 22, 2026
Artificial Analysis Intelligence Index (2026-08-14)	Winner: 60	52
SWE-bench Verified (2026-02)	80.6	Not verifiedUnverified
GPQA Diamond (2026-02)	94.3	Not verifiedUnverified
Humanity's Last Exam (2026-02)	44.4	Not verifiedUnverified
Terminal-Bench 2.1 (2026-07)	73.8	Not verifiedUnverified

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.
2026-02: 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. · Xiaomi MiMo-V2.5-Pro: $1.00/$3.00 per MTok up to 256K prompt; $2.00/$6.00 above 256K (to 1M). Open weights (MIT). 1.02T/42B active MoE, native multimodal.

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 2, 2026

Xiaomi MiMo-V2.5-Pro

MiMo-V2.5-Pro is Xiaomi's open-weight (MIT) 1.02T MoE with native multimodal and a 1M context.

Best for

Open-weight frontier
Multimodal
Long-context

Watch out

Verify weights/pricing on your endpoint.

When the cheaper one wins

Xiaomi MiMo-V2.5-Pro is cheaper on output at $3 per million tokens against $12 for Gemini 3.1 Pro — about 4.0×. 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.

Run the model picker

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.
1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
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.

Gemini 3.1 Pro: Google Cloud — Gemini 3.1 Pro (accessed 2026-08-29)
Gemini 3.1 Pro: TechCrunch — Gemini 3.1 Pro (accessed 2026-08-29)
Xiaomi MiMo-V2.5-Pro: Xiaomi — MiMo V2.5 (accessed 2026-08-29)
Xiaomi MiMo-V2.5-Pro: Xiaomi MiMo (accessed 2026-08-29)

Related comparisons

Diving deeper on one model? Gemini 3.1 Pro · Xiaomi MiMo-V2.5-Pro

Common questions

Gemini 3.1 Pro vs Xiaomi MiMo-V2.5-Pro

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

Is Gemini 3.1 Pro or Xiaomi MiMo-V2.5-Pro cheaper for input?

Xiaomi MiMo-V2.5-Pro is cheaper at $1 per million input tokens, against $2 for Gemini 3.1 Pro — roughly 2.0× 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. Xiaomi MiMo-V2.5-Pro has tiered pricing: $1.00/$3.00 per MTok up to 256K prompt; $2.00/$6.00 above 256K (to 1M). Open weights (MIT). 1.02T/42B active MoE, native multimodal.

Is Gemini 3.1 Pro or Xiaomi MiMo-V2.5-Pro cheaper for output?

Xiaomi MiMo-V2.5-Pro is cheaper at $3 per million output tokens, against $12 for Gemini 3.1 Pro — roughly 4.0× 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. Xiaomi MiMo-V2.5-Pro has tiered pricing: $1.00/$3.00 per MTok up to 256K prompt; $2.00/$6.00 above 256K (to 1M). Open weights (MIT). 1.02T/42B active MoE, native multimodal.

Which has the larger context window, Gemini 3.1 Pro or Xiaomi MiMo-V2.5-Pro?

Gemini 3.1 Pro accepts 1.05M tokens against 1M for Xiaomi MiMo-V2.5-Pro. This only matters if you routinely send very long documents or large codebases.

Do Gemini 3.1 Pro and Xiaomi MiMo-V2.5-Pro support the same reasoning levels?

Gemini 3.1 Pro exposes low, medium, high, while Xiaomi MiMo-V2.5-Pro exposes low, high, max.

Should I use Gemini 3.1 Pro or Xiaomi MiMo-V2.5-Pro?

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; Xiaomi MiMo-V2.5-Pro suits open-weight frontier.

Can I self-host Gemini 3.1 Pro or Xiaomi MiMo-V2.5-Pro?

Xiaomi MiMo-V2.5-Pro 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: Xiaomi MiMo-V2.5-Pro costs $1 per 1M tokens versus $2 for Gemini 3.1 Pro — a 2x difference at the headline tier.
Context: Gemini 3.1 Pro takes 1.05M against 1M for Xiaomi MiMo-V2.5-Pro — only decisive if your prompts approach the smaller window.
Measured capability: Gemini 3.1 Pro leads Artificial Analysis Intelligence Index 60 to 52 (measured 2026-08-14).
Deployment: Xiaomi MiMo-V2.5-Pro publishes weights you can self-host; the other is API-only.

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