# Codestral vs Qwen3-1.7B

> Codestral is the stronger model overall, scoring 30.6 to 26.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/codestral-vs-qwen3-1-7b
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- Qwen3-1.7B has downloadable open weights; the other is API-only.

## Snapshot

| | Codestral | Qwen3-1.7B |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 30.6 | 26.6 |
| Rank | 290 | 336 |
| Context | 256K | — |
| Input $/M | $0.30 | — |
| Output $/M | $0.90 | — |
| Weights | Proprietary | Open |

## Coding

- Codestral: 27.3 (#321)
- Qwen3-1.7B: —

| Benchmark | Codestral | Qwen3-1.7B |
|---|---|---|
| Aider Polyglot | 11.1% | — |
| BigCodeBench Instruct | 41.8% | — |
| BigCodeBench Complete | 52.5% | — |
| ALE-Bench | 137.78 | — |
| HumanEval+ | 73.8% | — |
| MBPP+ | 61.9% | — |

## Agentic & Tool Use

- Codestral: —
- Qwen3-1.7B: 24.7 (#115)

| Benchmark | Codestral | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |

## Reasoning

- Codestral: 19.8 (#251)
- Qwen3-1.7B: 19.2 (#267)

| Benchmark | Codestral | Qwen3-1.7B |
|---|---|---|
| Kagi LLM Benchmark | 32.5% | — |
| Chess Puzzles | — | 0% |

## Math

- Codestral: —
- Qwen3-1.7B: 16.3 (#294)

| Benchmark | Codestral | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 8.1% |

## Knowledge

- Codestral: —
- Qwen3-1.7B: 19.6 (#278)

| Benchmark | Codestral | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | — | 38% |

## FAQ

### Is Codestral better than Qwen3-1.7B?

Codestral is the stronger model overall, scoring 30.6 to 26.6 on the Noometry Index.

### How many benchmarks do Codestral and Qwen3-1.7B share?

0 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and Qwen3-1.7B has 4.