Model comparison
Mistral Nemo vs Qwen3.5 122B-A10B
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 26.4 on the Noometry Index. Mistral Nemo costs 7.3× less per token, which makes it the better buy when Qwen3.5 122B-A10B's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 1 benchmark with published results for both. Mistral Nemo scores higher in 0 categories and Qwen3.5 122B-A10B in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5 122B-A10B leads 60.0 to 28.5.
- The biggest single-benchmark swing is DTBench: 48.6% for Mistral Nemo and 84.3% for Qwen3.5 122B-A10B.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.40 / $3.20 for Qwen3.5 122B-A10B.
- Qwen3.5 122B-A10B accepts more context: 262K tokens versus 128K.
Side by side
| Mistral Nemo | Qwen3.5 122B-A10B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 26.4 | 42.1 |
| Released | 2024-07-01 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.15 | $0.40 |
| Output $ / M tokens | $0.15 | $3.20 |
| Results tracked | 10 | 27 |
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Category by category
Coding Not comparable
Mistral Nemo: —, Qwen3.5 122B-A10B: 39.1 (#162)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena WebDev | — | 1360 |
| SciCode | — | 35.6% |
| LMArena Coding | — | 1436 |
Agentic & Tool Use Not comparable
Mistral Nemo: 23.5 (#125), Qwen3.5 122B-A10B: —
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 27.6% | — |
| BALROG | 17.6% | — |
Reasoning Qwen3.5 122B-A10B leads
Mistral Nemo: 20.7 (#232), Qwen3.5 122B-A10B: 27.2 (#123)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| DTBench | 48.6% | 84.3% |
| NYT Connections (extended) | — | 51.7% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 51.2% |
| LMArena Hard Prompts | — | 1421 |
| Mystery Game Puzzles | — | 17% |
| LMCA | — | 32.2% |
| Epoch Capabilities Index | 118.68 | — |
| PIQA | 83.5% | — |
Math Qwen3.5 122B-A10B leads
Mistral Nemo: 25.5 (#268), Qwen3.5 122B-A10B: 39.1 (#112)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Math | — | 1432 |
| MATH Level 5 | 10.8% | — |
| GSM8K | 84.2% | — |
Knowledge Qwen3.5 122B-A10B leads
Mistral Nemo: 12.3 (#298), Qwen3.5 122B-A10B: 38.8 (#142)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| GPQA Diamond | 29.9% | — |
| Vectara Hallucination Rate | — | 11.2% |
| LMArena Expert | — | 1432 |
| BoolQ | 82.5% | — |
Multimodal Not comparable
Mistral Nemo: —, Qwen3.5 122B-A10B: 39.6 (#57)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Vision | — | 1245 |
Multilingual Not comparable
Mistral Nemo: —, Qwen3.5 122B-A10B: 51.6 (#107)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Non-English | — | 1400 |
| LMArena Chinese | — | 1462 |
| LMArena French | — | 1442 |
| LMArena German | — | 1426 |
| LMArena Japanese | — | 1367 |
| LMArena Korean | — | 1352 |
| LMArena Russian | — | 1400 |
| LMArena Spanish | — | 1424 |
Instruction Following Not comparable
Mistral Nemo: —, Qwen3.5 122B-A10B: 73.8 (#115)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Instruction Following | — | 1399 |
Long Context Not comparable
Mistral Nemo: —, Qwen3.5 122B-A10B: 43.0 (#109)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Longer Query | — | 1410 |
Writing & Preference Qwen3.5 122B-A10B leads
Mistral Nemo: 28.5 (#296), Qwen3.5 122B-A10B: 60.0 (#105)
| Benchmark | Mistral Nemo | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Text | — | 1417 |
| LMArena Creative Writing | — | 1368 |
| EQ-Bench Creative Writing | 881 | — |
| LMArena Multi-Turn | — | 1416 |
Frequently asked questions
Is Mistral Nemo better than Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 26.4 on the Noometry Index. Mistral Nemo costs 7.3× less per token, which makes it the better buy when Qwen3.5 122B-A10B's lead doesn't matter for your workload.
Which is cheaper, Mistral Nemo or Qwen3.5 122B-A10B?
Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; Qwen3.5 122B-A10B lists at $0.40 and $3.20.
Which has the bigger context window?
Qwen3.5 122B-A10B does, with 262K tokens against 128K.
How many benchmarks do Mistral Nemo and Qwen3.5 122B-A10B share?
1 benchmark has published results for both models. Mistral Nemo has 10 scored results on Noometry and Qwen3.5 122B-A10B has 27.