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Model comparison

Qwen 3.8 Max vs Xiaomi MiMo-V2.5-Pro

Qwen against Xiaomi, compared on context, price, and verified benchmark results.

Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Qwen

Qwen 3.8 Max

Frontier · Open weights

vs

Xiaomi

Xiaomi MiMo-V2.5-Pro

Frontier · Open weights

AI model capability comparison
SpecificationQwen 3.8 MaxXiaomi MiMo-V2.5-Pro
ProviderQwenXiaomi
TierFrontierFrontier
Context window991KWinner: 1M
Max output131KNot verifiedUnverified
Input / 1M tokens$2Winner: $1
Output / 1M tokens$6Winner: $3
WeightsOpenOpen
Parameters2.4T total / 95B active (MoE)1.02T total / 42B active (MoE)
Reasoning levelslow, high, maxlow, high, max
Modalitiestext, image, videotext, image
LicenseNot disclosedUnverifiedMIT
API model idqwen3.8-maxmimo-v2-5-pro
ReleasedAugust 3, 2026April 22, 2026
Artificial Analysis Intelligence Index (2026-08-14)Winner: 5852
Terminal-Bench 2.1 (2026-08-03)86.6Not verifiedUnverified
GPQA Diamond (2026-08-03)92.6Not verifiedUnverified
Humanity's Last Exam (2026-08-14)56.2Not verifiedUnverified
SWE-bench Verified (2026-09-01)85.6Not 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

  • 2026-09-01: vals.ai SWE-bench Verified leaderboard (independent, mini-swe-agent bash-only); not published by Qwen (official used SWE-bench Pro 67.7)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.
  • 2026-08-14: Z.ai GLM-5.3 blog (independent Z.ai-run, with tools; Qwen official no-tools 43.6 — both preserved)Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise. Comparability: comparable with caveat — Subset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.
  • 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).
  • 2026-08-03: Qwen official blog (vendor-run table)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.

Pricing tiers: Qwen 3.8 Max: $2/$6 per MTok (Alibaba Cloud Model Studio). Weights announced open, verify they have dropped. · 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.

FrontierOpen weightsRecord checked September 3, 2026

Qwen 3.8 Max

Qwen 3.8 Max is Alibaba's flagship — 2.4T MoE with 1M-class context, near frontier on the Intelligence Index.

Best for

  • Open-weight frontier work
  • Long-context
  • Multimodal

Watch out

Open weights dropped 2026-08-12 under a custom (non-Apache) licence with vision and 1M-context stripped from the open checkpoint — the open checkpoint is not the full API model. Verify the licence before commercial use.

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 $6 for Qwen 3.8 Max — about 2.0×. 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.

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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.
  • 4/5 core specs verified on both sides — Not published for at least one side: max output.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 8 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? Qwen 3.8 Max · Xiaomi MiMo-V2.5-Pro

Common questions

Qwen 3.8 Max vs Xiaomi MiMo-V2.5-Pro

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

Is Qwen 3.8 Max 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 Qwen 3.8 Max — 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; Qwen 3.8 Max has tiered pricing: $2/$6 per MTok (Alibaba Cloud Model Studio). Weights announced open, verify they have dropped. 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 Qwen 3.8 Max or Xiaomi MiMo-V2.5-Pro cheaper for output?

Xiaomi MiMo-V2.5-Pro is cheaper at $3 per million output tokens, against $6 for Qwen 3.8 Max — 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; Qwen 3.8 Max has tiered pricing: $2/$6 per MTok (Alibaba Cloud Model Studio). Weights announced open, verify they have dropped. 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, Qwen 3.8 Max or Xiaomi MiMo-V2.5-Pro?

Xiaomi MiMo-V2.5-Pro accepts 1M tokens against 991K for Qwen 3.8 Max. This only matters if you routinely send very long documents or large codebases.

Do Qwen 3.8 Max and Xiaomi MiMo-V2.5-Pro support the same reasoning levels?

Yes — both accept the same effort settings: "low", "high", "max". Higher effort costs more and takes longer, so start low and raise it only where output quality actually improves.

Should I use Qwen 3.8 Max 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. Qwen 3.8 Max suits open-weight frontier work; Xiaomi MiMo-V2.5-Pro suits open-weight frontier.

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 Qwen 3.8 Max — a 2x difference at the headline tier.
  • Context: Xiaomi MiMo-V2.5-Pro takes 1M against 991K for Qwen 3.8 Max — only decisive if your prompts approach the smaller window.
  • Measured capability: Qwen 3.8 Max leads Artificial Analysis Intelligence Index 58 to 52 (measured 2026-08-14).
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