Model decision surface
Compare AI models
Start with Gemma 3 4B and Codestral 2508, 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
Gemma 3 4B vs Codestral 2508
Live dataset updated 8/18/2026, 3:23:39 AM UTC
Open 1200×630 evidence receipt| Field | Gemma 3 4B | Codestral 2508 Mistral AI |
|---|---|---|
| ModelCap position | #197 | #229 |
| Index score | 10.9 | 0.0 |
| Evidence | Measured3 public benchmark observations across 3 boards | Estimatedpublisher corpus prior · leave-one-anchor-out calibrated |
| Input / 1M | $0.05 | $0.30 |
| Output / 1M | $0.10 | $0.90 |
| Pricing status | fresh | fresh |
| Context | 131K | 256K |
| Providers | 1 | 1 |
| Weight access | Gated access | API only |
Decision facts
- Gemma 3 4B is #197; Codestral 2508 is #229 on the same current language board.
- Index scores are 10.9 for Gemma 3 4B and 0.0 for Codestral 2508.
- Evidence differs: Gemma 3 4B is Measured; Codestral 2508 is Estimated.
- Listed output price per 1M tokens is $0.10 for Gemma 3 4B and $0.90 for Codestral 2508.
- Published context is 131,072 tokens for Gemma 3 4B and 256,000 for Codestral 2508.
- Weight access differs: Gemma 3 4B is gated; Codestral 2508 is none.
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.