Compare / Qwen3-14B vs Mistral Large 2.1 (2411)
Qwen3-14B vs Mistral Large 2.1 (2411)
Which is cheaper, which is more capable, and which does better at each kind of work, from 13 results on 3 sources that measured both models.
Of the 13 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.
Results as of 9 October 2026 (catalogue release 2026-10-09-dd620e778ac5). See also Alibaba vs Mistral AI, every model from both labs.
Qwen3-14B or Mistral Large 2.1 (2411)? The short answer
They score and cost about the same: pick on the results below that match your work.
- Qwen3-14B is newer: released 28 Apr 2025, against 18 Nov 2024 for Mistral Large 2.1 (2411).
- On third-party benchmarks, on the results both models have: Qwen3-14B does better for agents and tool use; Mistral Large 2.1 (2411) for writing and sticking to the facts.
Head to head
Every fact side by side
| Qwen3-14B | Mistral Large 2.1 (2411) | |
|---|---|---|
| Price per million tokens | $0.12 in · $0.24 out | Not on sale |
| Blended (3 in : 1 out) | $0.15 | – |
| Cheapest host, blended | $0.13 (NextBit, INT4) | – |
| Intelligence Index | 8.2 | – |
| Spring Prompt overall | – | – |
| Output speed, tokens a second | – | – |
| Context window | 131,072 tokens | – |
| Released | 28 Apr 2025 (newer) | 18 Nov 2024 |
| Weights | Open | Closed |
| Developer based in | China | France |
Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.
Which is better for what
Each model's rank among the models on sale today, for each kind of work, from our own benchmarks and licensed sources. Further right is better; the better rank is in green.
Every shared result
Each model's best result on every measure both have, grouped by benchmark, with the setting that produced it. Under each measure, every model that benchmark has measured is a grey tick, best to the right, so you can see where the two sit in the field. The headline measures of each benchmark come first; the rest are under "Show all". Green marks the better value; where a source reports ranges that overlap, neither is marked.
| Measure | Qwen3-14B | Mistral Large 2.1 (2411) |
|---|---|---|
| Berkeley Function Calling Leaderboard (BFCL) V4 reported by Berkeley Function Calling Leaderboard (BFCL) V4 · 3 results | ||
| Overall accuracy · BFCL% correct, higher is better 34 · 35 of 81 measured | 41.0%bfcl fc | 38.4%bfcl fc |
| Irrelevance detection · BFCL% correct, higher is better 20 · 64 of 81 measured | 87.2%bfcl prompt | 68.9%bfcl fc |
| Memory · BFCL% correct, higher is better 33 · 23 of 81 measured | 19.6%bfcl fc | 25.0%bfcl fc |
| UGI Leaderboard reported by UGI Leaderboard · 3 results | ||
| Writing score · UGIscore out of 100, higher is better 128 · 118 of 230 measured | 34.8no reasoning | 37.8 |
| Requested-length error · UGI% off the requested word count, lower is better 111 · 49 of 230 measured | 20.0%no reasoning | 11.0% |
| Style adherence · UGIscore from 0 to 1, higher is better 49 · 55 of 230 measured | 0.37no reasoning | 0.37 |
| Vectara Hallucination Leaderboard reported by Vectara Hallucination Leaderboard · 2 results | ||
| Hallucination rate · Vectara% of summaries, lower is better 17 · 8 of 104 measured | 5.4% | 4.5% |
| Answer rate · Vectara% of documents, higher is better 17 · 17 of 104 measured | 99.9% | 99.9% |
Show all 13 results (5 more)
| Measure | Qwen3-14B | Mistral Large 2.1 (2411) |
|---|---|---|
| Berkeley Function Calling Leaderboard (BFCL) V4 reported by Berkeley Function Calling Leaderboard (BFCL) V4 · 5 results | ||
| Multi-turn tasks · BFCL% correct, higher is better 31 · 46 of 81 measured | 34.8%bfcl fc | 14.1%bfcl fc |
| Relevance detection · BFCL% correct, higher is better 26 · 8 of 81 measured | 87.5%bfcl fc | 93.8%bfcl fc |
| Single-turn calls (curated) · BFCL% correct, higher is better 7 · 40 of 81 measured | 89.5%bfcl prompt | 84.7%bfcl fc |
| Single-turn calls (user-contributed) · BFCL% correct, higher is better 10 · 4 of 81 measured | 80.0%bfcl fc | 81.9%bfcl fc |
| Web search · BFCL% correct, higher is better 37 · 25 of 81 measured | 10.5%bfcl prompt | 28.0%bfcl fc |
Compare them with other models
Quick answers
Is Qwen3-14B better than Mistral Large 2.1 (2411)?
They score and cost about the same: pick on the results below that match your work.
Which is better for agents and tool use, Qwen3-14B or Mistral Large 2.1 (2411)?
Mistral Large 2.1 (2411) ranks 81 of 164 models on sale for multi-step tasks with tools: support desks, coding agents, function calls, against 122 for Qwen3-14B.
Which is better for writing, Qwen3-14B or Mistral Large 2.1 (2411)?
Qwen3-14B ranks 130 of 188 models on sale for what people prefer in blind comparisons, and judged writing quality, against 142 for Mistral Large 2.1 (2411).
Which is better for sticking to the facts, Qwen3-14B or Mistral Large 2.1 (2411)?
Mistral Large 2.1 (2411) ranks 6 of 152 models on sale for summarising without inventing things, and factual answers, against 15 for Qwen3-14B.
Run Qwen3-14B and Mistral Large 2.1 (2411) on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.