Model comparison
Mistral Nemo vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 26.4 on the Noometry Index. Mistral Nemo costs 4.1× less per token, which makes it the better buy when Qwen3 14B'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 1 category and Qwen3 14B in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 14B leads 39.3 to 12.3.
- The biggest single-benchmark swing is GPQA Diamond: 29.9% for Mistral Nemo and 63.8% for Qwen3 14B.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- Qwen3 14B accepts more context: 131K tokens versus 128K.
Side by side
| Mistral Nemo | Qwen3 14B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 26.4 | 35.5 |
| Released | 2024-07-01 | 2025-04 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $0.15 | $0.35 |
| Output $ / M tokens | $0.15 | $1.40 |
| Results tracked | 10 | 12 |
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Category by category
Coding Not comparable
Mistral Nemo: —, Qwen3 14B: 37.3 (#195)
| Benchmark | Mistral Nemo | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
Agentic & Tool Use Qwen3 14B leads
Mistral Nemo: 23.5 (#125), Qwen3 14B: 29.6 (#83)
| Benchmark | Mistral Nemo | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 27.6% | 41% |
| BALROG | 17.6% | — |
Reasoning Mistral Nemo leads
Mistral Nemo: 20.7 (#232), Qwen3 14B: 18.5 (#280)
| Benchmark | Mistral Nemo | Qwen3 14B |
|---|---|---|
| DTBench | 48.6% | 64% |
| Epoch Capabilities Index | 118.68 | 138.23 |
| Kagi LLM Benchmark | — | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| LMCA | — | 18.2% |
| PIQA | 83.5% | — |
Math Qwen3 14B leads
Mistral Nemo: 25.5 (#268), Qwen3 14B: 38.6 (#133)
| Benchmark | Mistral Nemo | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| MATH Level 5 | 10.8% | — |
| GSM8K | 84.2% | — |
Knowledge Qwen3 14B leads
Mistral Nemo: 12.3 (#298), Qwen3 14B: 39.3 (#134)
| Benchmark | Mistral Nemo | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 29.9% | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
| BoolQ | 82.5% | — |
Long Context Not comparable
Mistral Nemo: —, Qwen3 14B: 38.1 (#204)
| Benchmark | Mistral Nemo | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
Writing & Preference Not comparable
Mistral Nemo: 28.5 (#296), Qwen3 14B: —
| Benchmark | Mistral Nemo | Qwen3 14B |
|---|---|---|
| EQ-Bench Creative Writing | 881 | — |
Frequently asked questions
Is Mistral Nemo better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 26.4 on the Noometry Index. Mistral Nemo costs 4.1× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Which is cheaper, Mistral Nemo or Qwen3 14B?
Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Which has the bigger context window?
Qwen3 14B does, with 131K tokens against 128K.
How many benchmarks do Mistral Nemo and Qwen3 14B share?
4 benchmarks have published results for both models. Mistral Nemo has 10 scored results on Noometry and Qwen3 14B has 12.