Mistral Small 3.1 vs Qwen3.8-Flash-Next
Which is better for the money: Mistral Small 3.1 by Mistral or Qwen3.8-Flash-Next by Alibaba? Intelligence, total benchmark cost, and end-to-end time from Artificial Analysis & other sources, snapshot 2026-10-26.
Trade-off
Verdict
Depends on your budget
Qwen3.8-Flash-Next scores 32.7 points higher (39.8 vs 7.1) but costs 13× as much to run the benchmark ($363 vs $27.8; mid-range vs budget cost classes). They are not alternatives at one budget: pick Qwen3.8-Flash-Next when you need intelligence above 7.1, and Mistral Small 3.1 when 7.1 is enough.
| Metric | Mistral Small 3.1 | Qwen3.8-Flash-Next | Difference |
|---|---|---|---|
| Intelligence (higher is better) | 7.1 | 39.8 | +460.6% Qwen3.8-Flash-Next is 5.6× more intelligent |
| Total AA cost (lower is better) | $27.82 | $362.72 | +1203.8% Qwen3.8-Flash-Next is 13× more expensive |
| End-to-end time (lower is better) | 10.95s | 50.51s | +361.3% Qwen3.8-Flash-Next is 361.3% slower |
| Price per 1M tokens (in / out) | $0.08 / $0.14 | $0.15 / $0.47 | |
| Input modalities | Text, Image | Text, Image, Video |
Qwen3.8-Flash-Next vs Mistral Small 3.1: 460.6% more intelligence, 1203.8% more cost to run the AA benchmark, and 361.3% slower end-to-end.
Today's Pareto frontier
Against the frontier
- Mistral Small 3.1 is off the frontier: at the same or lower cost, GPT-6 Luna (Low) scores 21.50 for $10.6.
- Qwen3.8-Flash-Next is off the frontier: at the same or lower cost, GPT-6.1 Sol (Medium) scores 47.80 for $361.
Mistral Small 3.1Qwen3.8-Flash-NextToday's Pareto frontierOpen-weights frontierEvery other model
Matchup
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Accept: text/markdown or ?format=md returns this page as Markdown. JSON: /api/v1/compare/mistral-small-3-1/qwen3-8-flash-next · Markdown: /api/v1/compare/mistral-small-3-1/qwen3-8-flash-next?format=md · llms.txt · agent skill