Model decision surface
Compare AI models
Start with Mistral Small 4 and Qwen3.5-9B, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
Mistral Small 4 vs Qwen3.5-9B
Live dataset updated 9/9/2026, 9:50:24 PM UTC
Open 1200×630 evidence receipt| Field | Mistral Small 4 Mistral AI | Qwen3.5-9B Qwen |
|---|---|---|
| ModelCap position | #97 | #96 |
| Index score | 42.0 | 42.2 |
| Evidence | Measured1 public benchmark observation across 1 board | Estimatedpublisher-corpus-prior over 180 held-out anchors (31%); launch card against 3 resolved peers on 10 rows (69%); exceeds every named peer on 4 of 10 rows; optimism haircut 0.6 from cross-lab-probe; shrunk 3.8 up toward the measured corpus |
| Input / 1M | $0.15 | $0.10 |
| Output / 1M | $0.60 | $0.15 |
| Pricing status | fresh | fresh |
| Context | 262K | 262K |
| Providers | 2 | 6 |
| Weight access | Open weights | Open weights |
Decision facts
- Mistral Small 4 is #97; Qwen3.5-9B is #96 on the same current language board.
- Index scores are 42.0 for Mistral Small 4 and 42.2 for Qwen3.5-9B. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Mistral Small 4 is Measured; Qwen3.5-9B is Estimated.
- Listed output price per 1M tokens is $0.60 for Mistral Small 4 and $0.15 for Qwen3.5-9B. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.60 for Mistral Small 4 versus $0.27 for Qwen3.5-9B. Qwen3.5-9B costs 54.2% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
- Published context is 262,144 tokens for Mistral Small 4 and 262,144 for Qwen3.5-9B.
- ModelCap currently lists 2 providers for Mistral Small 4 and 6 for Qwen3.5-9B.
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
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Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.