Model comparison
DeepSeek-V3.1-Terminus vs Qwen3 Max
DeepSeek-V3.1-Terminus and Qwen3 Max score almost the same on the Noometry Index (42.6 vs 43.5), so choose on price, context window or the category you care about most.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 2 categories and Qwen3 Max in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.1-Terminus leads 25.7 to 22.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 57.4% for DeepSeek-V3.1-Terminus and 72.5% for Qwen3 Max.
- DeepSeek-V3.1-Terminus is cheaper at $0.30 / $1 per million input/output tokens, against $1.20 / $6 for Qwen3 Max.
- Qwen3 Max accepts more context: 262K tokens versus 164K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | Qwen3 Max | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 42.6 | 43.5 |
| Released | 2025-09-22 | 2025-09-23 |
| Weights | Open | Proprietary |
| Context window | 164K | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.30 | $1.20 |
| Output $ / M tokens | $1 | $6 |
| Results tracked | 16 | 33 |
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Category by category
Coding Too close to call
DeepSeek-V3.1-Terminus: 41.5 (#114), Qwen3 Max: 42.4 (#93)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| LMArena Coding | 1426 | 1456 |
| ALE-Bench | 745.17 | 370.45 |
| SciCode | 40.6% | — |
Agentic & Tool Use Not comparable
DeepSeek-V3.1-Terminus: —, Qwen3 Max: —
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| Vending-Bench 2 | — | 71.56 |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 25.7 (#126), Qwen3 Max: 22.0 (#186)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 72.5% |
| LMArena Hard Prompts | 1427 | 1448 |
| DTBench | 81.3% | 82.1% |
| LMCA | 28.6% | 28.3% |
| NYT Connections (extended) | — | 30.1% |
| CritPt | 1.7% | — |
| Chess Puzzles | — | 4% |
| Mystery Game Puzzles | — | 5% |
| Epoch Capabilities Index | — | 142.41 |
Math Qwen3 Max leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Qwen3 Max: 37.6 (#94)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| LMArena Math | 1402 | 1447 |
| FrontierMath (Tiers 1-3) | — | 18.9% |
| OTIS Mock AIME 2024-2025 | — | 73.3% |
| MATH Level 5 | — | 97.1% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Qwen3 Max: 48.1 (#72)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| GPQA Diamond | — | 72.6% |
| SimpleQA Verified | — | 48.7% |
| LMArena Expert | — | 1457 |
Multilingual Qwen3 Max leads
DeepSeek-V3.1-Terminus: 52.3 (#87), Qwen3 Max: 53.9 (#58)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| LMArena Non-English | 1407 | 1429 |
| LMArena Russian | 1434 | 1428 |
| LMArena Chinese | — | 1479 |
| LMArena French | — | 1450 |
| LMArena German | — | 1463 |
| LMArena Japanese | — | 1399 |
| LMArena Korean | — | 1397 |
| LMArena Spanish | — | 1463 |
Instruction Following Too close to call
DeepSeek-V3.1-Terminus: 74.4 (#96), Qwen3 Max: 75.0 (#81)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| LMArena Instruction Following | 1406 | 1420 |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.5 (#88), Qwen3 Max: 41.6 (#129)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| LMArena Longer Query | 1426 | 1439 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 14.5% |
Writing & Preference Qwen3 Max leads
DeepSeek-V3.1-Terminus: 61.3 (#87), Qwen3 Max: 62.6 (#72)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3 Max |
|---|---|---|
| LMArena Text | 1420 | 1439 |
| LMArena Creative Writing | 1404 | 1401 |
| LMArena Multi-Turn | 1411 | 1446 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Qwen3 Max?
DeepSeek-V3.1-Terminus and Qwen3 Max score almost the same on the Noometry Index (42.6 vs 43.5), so choose on price, context window or the category you care about most.
Which is cheaper, DeepSeek-V3.1-Terminus or Qwen3 Max?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.30 per million input tokens and $1 per million output tokens; Qwen3 Max lists at $1.20 and $6.
Is DeepSeek-V3.1-Terminus or Qwen3 Max better for coding?
They score almost the same on coding (41.5 vs 42.4); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3 Max does, with 262K tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Qwen3 Max share?
14 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Qwen3 Max has 33.