Model comparison
Mistral Nemo vs Qwen2.5 7B Instruct
Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 26.4 on the Noometry Index. Mistral Nemo costs 2.0× less per token, which makes it the better buy when Qwen2.5 7B Instruct's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. Mistral Nemo scores higher in 2 categories and Qwen2.5 7B Instruct in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen2.5 7B Instruct leads 48.8 to 28.5.
- The biggest single-benchmark swing is BALROG: 17.6% for Mistral Nemo and 7.8% for Qwen2.5 7B Instruct.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.17 / $0.70 for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct accepts more context: 131K tokens versus 128K.
Side by side
| Mistral Nemo | Qwen2.5 7B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 26.4 | 29.0 |
| Released | 2024-07-01 | 2024-09 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $0.15 | $0.17 |
| Output $ / M tokens | $0.15 | $0.70 |
| Results tracked | 10 | 15 |
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Category by category
Coding Not comparable
Mistral Nemo: —, Qwen2.5 7B Instruct: 36.5 (#208)
| Benchmark | Mistral Nemo | Qwen2.5 7B Instruct |
|---|---|---|
| BigCodeBench Instruct | — | 37.6% |
| BigCodeBench Complete | — | 46.1% |
Agentic & Tool Use Too close to call
Mistral Nemo: 23.5 (#125), Qwen2.5 7B Instruct: 23.8 (#124)
| Benchmark | Mistral Nemo | Qwen2.5 7B Instruct |
|---|---|---|
| BALROG | 17.6% | 7.8% |
| Berkeley Function Calling Leaderboard | 27.6% | — |
Reasoning Mistral Nemo leads
Mistral Nemo: 20.7 (#232), Qwen2.5 7B Instruct: 14.8 (#322)
| Benchmark | Mistral Nemo | Qwen2.5 7B Instruct |
|---|---|---|
| DTBench | 48.6% | 47.7% |
| Epoch Capabilities Index | 118.68 | 118.51 |
| Chess Puzzles | — | 0% |
| LMCA | — | 6.4% |
| PIQA | 83.5% | — |
Math Mistral Nemo leads
Mistral Nemo: 25.5 (#268), Qwen2.5 7B Instruct: 12.6 (#306)
| Benchmark | Mistral Nemo | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.5% |
| Omni-MATH | — | 29.4% |
| MATH Level 5 | 10.8% | — |
| GSM8K | 84.2% | — |
Knowledge Qwen2.5 7B Instruct leads
Mistral Nemo: 12.3 (#298), Qwen2.5 7B Instruct: 17.0 (#286)
| Benchmark | Mistral Nemo | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 29.9% | 35.5% |
| MMLU-Pro | — | 53.9% |
| GPQA (HELM) | — | 34.1% |
| BoolQ | 82.5% | — |
| MMLU | — | 72.9% |
Instruction Following Not comparable
Mistral Nemo: —, Qwen2.5 7B Instruct: 63.2 (#231)
| Benchmark | Mistral Nemo | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
Writing & Preference Qwen2.5 7B Instruct leads
Mistral Nemo: 28.5 (#296), Qwen2.5 7B Instruct: 48.8 (#195)
| Benchmark | Mistral Nemo | Qwen2.5 7B Instruct |
|---|---|---|
| EQ-Bench Creative Writing | 881 | — |
| WildBench | — | 73.1% |
Frequently asked questions
Is Mistral Nemo better than Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 26.4 on the Noometry Index. Mistral Nemo costs 2.0× less per token, which makes it the better buy when Qwen2.5 7B Instruct's lead doesn't matter for your workload.
Which is cheaper, Mistral Nemo or Qwen2.5 7B Instruct?
Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; Qwen2.5 7B Instruct lists at $0.17 and $0.70.
Which has the bigger context window?
Qwen2.5 7B Instruct does, with 131K tokens against 128K.
How many benchmarks do Mistral Nemo and Qwen2.5 7B Instruct share?
4 benchmarks have published results for both models. Mistral Nemo has 10 scored results on Noometry and Qwen2.5 7B Instruct has 15.