Model comparison
DeepSeek-V3.1-Terminus vs Qwen3-4B
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where DeepSeek-V3.1-Terminus leads 25.7 to 18.5.
Side by side
| DeepSeek-V3.1-Terminus | Qwen3-4B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 42.6 | 31.5 |
| Released | 2025-09-22 | 2025-04-29 |
| Weights | Open | Open |
| Context window | 164K | — |
| Max output | 66K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 16 | 6 |
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Category by category
Coding Not comparable
DeepSeek-V3.1-Terminus: 41.5 (#114), Qwen3-4B: —
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| SciCode | 40.6% | — |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |
Agentic & Tool Use Not comparable
DeepSeek-V3.1-Terminus: —, Qwen3-4B: 27.3 (#94)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 35.7% |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 25.7 (#126), Qwen3-4B: 18.5 (#264)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1427 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Qwen3-4B: 28.5 (#228)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 38.5% |
| OTIS Mock AIME 2024-2025 | — | 52.2% |
| LMArena Math | 1402 | — |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Qwen3-4B: 33.0 (#198)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| GPQA Diamond | — | 52.3% |
| Vectara Hallucination Rate | — | 5.7% |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.3 (#87), Qwen3-4B: —
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1434 | — |
Instruction Following Not comparable
DeepSeek-V3.1-Terminus: 74.4 (#96), Qwen3-4B: —
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| LMArena Instruction Following | 1406 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.5 (#88), Qwen3-4B: —
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| LMArena Longer Query | 1426 | — |
Writing & Preference Not comparable
DeepSeek-V3.1-Terminus: 61.3 (#87), Qwen3-4B: —
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3-4B |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1404 | — |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Qwen3-4B?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.5 on the Noometry Index.
How many benchmarks do DeepSeek-V3.1-Terminus and Qwen3-4B share?
0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Qwen3-4B has 6.