Model comparison
Mistral Nemo vs Qwen3.6 35B-A3B
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.2 to 25.9 on the Noometry Index. Mistral Nemo costs 3.7× less per token, which makes it the better buy when Qwen3.6 35B-A3B's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Mistral Nemo scores higher in 1 category and Qwen3.6 35B-A3B in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 35B-A3B leads 51.4 to 12.3.
- The biggest single-benchmark swing is GPQA Diamond: 29.9% for Mistral Nemo and 84.8% for Qwen3.6 35B-A3B.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.25 / $1.49 for Qwen3.6 35B-A3B.
- Qwen3.6 35B-A3B accepts more context: 262K tokens versus 128K.
Side by side
| Mistral Nemo | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 25.9 | 37.2 |
| Released | 2024-07-01 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.15 | $0.25 |
| Output $ / M tokens | $0.15 | $1.49 |
| Results tracked | 10 | 14 |
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Category by category
Coding Not comparable
Mistral Nemo: —, Qwen3.6 35B-A3B: 36.7 (#190)
Agentic & Tool Use Mistral Nemo leads
Mistral Nemo: 23.3 (#118), Qwen3.6 35B-A3B: 21.9 (#126)
| Benchmark | Mistral Nemo | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
| Berkeley Function Calling Leaderboard | 27.6% | — |
| BALROG | 17.6% | — |
Reasoning Qwen3.6 35B-A3B leads
Mistral Nemo: 19.9 (#230), Qwen3.6 35B-A3B: 27.2 (#112)
| Benchmark | Mistral Nemo | Qwen3.6 35B-A3B |
|---|---|---|
| DTBench | 48.6% | 73.9% |
| Epoch Capabilities Index | 118.63 | 143.92 |
| NYT Connections (extended) | — | 41.6% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 26% |
| Mystery Game Puzzles | — | 22% |
| LMCA | — | 29.7% |
| Surface Evolver Bench | — | 44.4% |
| PIQA | 83.5% | — |
Math Qwen3.6 35B-A3B leads
Mistral Nemo: 23.5 (#263), Qwen3.6 35B-A3B: 37.9 (#90)
| Benchmark | Mistral Nemo | Qwen3.6 35B-A3B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 20.4% |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
| MATH Level 5 | 10.8% | — |
| GSM8K | 84.2% | — |
Knowledge Qwen3.6 35B-A3B leads
Mistral Nemo: 12.3 (#293), Qwen3.6 35B-A3B: 51.4 (#63)
| Benchmark | Mistral Nemo | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | 29.9% | 84.8% |
| BoolQ | 82.5% | — |
Writing & Preference Not comparable
Mistral Nemo: 28.6 (#291), Qwen3.6 35B-A3B: —
| Benchmark | Mistral Nemo | Qwen3.6 35B-A3B |
|---|---|---|
| EQ-Bench Creative Writing | 881 | — |
Frequently asked questions
Is Mistral Nemo better than Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.2 to 25.9 on the Noometry Index. Mistral Nemo costs 3.7× less per token, which makes it the better buy when Qwen3.6 35B-A3B's lead doesn't matter for your workload.
Which is cheaper, Mistral Nemo or Qwen3.6 35B-A3B?
Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; Qwen3.6 35B-A3B lists at $0.25 and $1.49.
Which has the bigger context window?
Qwen3.6 35B-A3B does, with 262K tokens against 128K.
How many benchmarks do Mistral Nemo and Qwen3.6 35B-A3B share?
3 benchmarks have published results for both models. Mistral Nemo has 10 scored results on Noometry and Qwen3.6 35B-A3B has 14.