Compare · ModelsLive · 2 picked · head to head
Mistral Medium 3.5 vs Qwen3.7 Plus
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Qwen3.7 Plus wins on 16/17 benchmarks
Qwen3.7 Plus wins 16 of 17 shared benchmarks. Leads in speed · arena · general.
Category leads
speed·Qwen3.7 Plusarena·Qwen3.7 Plusgeneral·Qwen3.7 Pluscoding·Qwen3.7 Plus
Hype vs Reality
Attention vs performance
Mistral Medium 3.5
#250 by perf·no signal
Qwen3.7 Plus
#183 by perf·#2 by attention
Best value
Qwen3.7 Plus
7.8x better value than Mistral Medium 3.5
Mistral Medium 3.5
6.6 pts/$
$4.50/M
Qwen3.7 Plus
51.5 pts/$
$0.80/M
Vendor risk
Who is behind the model
Mistral AI
$14.0B·Tier 1
Alibaba (Qwen)
$293.0B·Tier 1
Head to head
17 benchmarks · 2 models
Mistral Medium 3.5Qwen3.7 Plus
Artificial Analysis · Agentic Index
Qwen3.7 Plus leads by +1.8
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
Mistral Medium 3.5
19.0
Qwen3.7 Plus
20.8
Artificial Analysis · Coding Index
Qwen3.7 Plus leads by +9.0
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
Mistral Medium 3.5
46.9
Qwen3.7 Plus
55.9
Artificial Analysis · CritPt
Qwen3.7 Plus leads by +9.1
Mistral Medium 3.5
0.0
Qwen3.7 Plus
9.1
Artificial Analysis · GDPval
Qwen3.7 Plus leads by +0.4
Mistral Medium 3.5
12.4
Qwen3.7 Plus
12.8
Artificial Analysis · GPQA Diamond
Qwen3.7 Plus leads by +15.2
Mistral Medium 3.5
74.8
Qwen3.7 Plus
90.0
Artificial Analysis · Humanity's Last Exam
Qwen3.7 Plus leads by +21.8
Mistral Medium 3.5
13.8
Qwen3.7 Plus
35.6
Artificial Analysis · IFBench
Qwen3.7 Plus leads by +9.2
Mistral Medium 3.5
68.8
Qwen3.7 Plus
78.0
Artificial Analysis · Long Context Reasoning
Qwen3.7 Plus leads by +3.7
Mistral Medium 3.5
69.3
Qwen3.7 Plus
73.0
Artificial Analysis · MMMU Pro
Qwen3.7 Plus leads by +15.6
Mistral Medium 3.5
64.9
Qwen3.7 Plus
80.5
Artificial Analysis · Quality Index
Qwen3.7 Plus leads by +11.0
Mistral Medium 3.5
14.2
Qwen3.7 Plus
25.2
Artificial Analysis · SciCode
Qwen3.7 Plus leads by +5.9
Mistral Medium 3.5
40.2
Qwen3.7 Plus
46.1
Artificial Analysis · tau2-Bench Telecom
Mistral Medium 3.5 leads by +1.2
Mistral Medium 3.5
94.2
Qwen3.7 Plus
93.0
Artificial Analysis · Terminal-Bench Hard
Qwen3.7 Plus leads by +13.7
Mistral Medium 3.5
33.3
Qwen3.7 Plus
47.0
Chatbot Arena Elo · Overall
Qwen3.7 Plus leads by +28.8
Mistral Medium 3.5
1426.9
Qwen3.7 Plus
1455.8
Dtbench
Qwen3.7 Plus leads by +14.2
Mistral Medium 3.5
59.1
Qwen3.7 Plus
73.3
Frontiercode
Qwen3.7 Plus leads by +2.2
Mistral Medium 3.5
8.0
Qwen3.7 Plus
10.2
Lmca
Qwen3.7 Plus leads by +13.6
Mistral Medium 3.5
30.7
Qwen3.7 Plus
44.2
Full benchmark table
| Benchmark | Mistral Medium 3.5 | Qwen3.7 Plus |
|---|---|---|
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 19.0 | 20.8 |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 46.9 | 55.9 |
Artificial Analysis · CritPt | 0.0 | 9.1 |
Artificial Analysis · GDPval | 12.4 | 12.8 |
Artificial Analysis · GPQA Diamond | 74.8 | 90.0 |
Artificial Analysis · Humanity's Last Exam | 13.8 | 35.6 |
Artificial Analysis · IFBench | 68.8 | 78.0 |
Artificial Analysis · Long Context Reasoning | 69.3 | 73.0 |
Artificial Analysis · MMMU Pro | 64.9 | 80.5 |
Artificial Analysis · Quality Index | 14.2 | 25.2 |
Artificial Analysis · SciCode | 40.2 | 46.1 |
Artificial Analysis · tau2-Bench Telecom | 94.2 | 93.0 |
Artificial Analysis · Terminal-Bench Hard | 33.3 | 47.0 |
Chatbot Arena Elo · Overall | 1426.9 | 1455.8 |
Dtbench | 59.1 | 73.3 |
Frontiercode | 8.0 | 10.2 |
Lmca | 30.7 | 44.2 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $1.50 | $7.50 | 262K tokens (~131 books) | $30.00 | |
| $0.32 | $1.28 | 1.0M tokens (~500 books) | $5.60 |