Model comparison
DeepSeek-V2.5 (Sep 2024) vs Qwen1.5 4b Chat
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 28.8 on the Noometry Index.
Last verified . 13 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 8 categories and Qwen1.5 4b Chat in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V2.5 (Sep 2024) leads 49.8 to 23.8.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 37.6 | 28.8 |
| Released | 2024-09-06 | — |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 22 | 13 |
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Category by category
Coding DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 31.7 (#281), Qwen1.5 4b Chat: 29.1 (#308)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Coding | 1309 | 999 |
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Reasoning DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 25.6 (#145), Qwen1.5 4b Chat: 18.5 (#279)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Hard Prompts | 1289 | 976 |
Math DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 35.9 (#177), Qwen1.5 4b Chat: 30.4 (#234)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Math | 1288 | 1026 |
Knowledge DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 34.8 (#193), Qwen1.5 4b Chat: 26.7 (#255)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Expert | 1266 | 980 |
Multilingual DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 42.5 (#193), Qwen1.5 4b Chat: 24.1 (#290)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Non-English | 1273 | 979 |
| LMArena Chinese | 1318 | 1024 |
| LMArena German | 1258 | 902 |
| LMArena Russian | 1289 | 952 |
| LMArena French | 1289 | — |
| LMArena Japanese | 1228 | — |
| LMArena Korean | 1209 | — |
| LMArena Spanish | 1248 | — |
Instruction Following DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 67.5 (#194), Qwen1.5 4b Chat: 49.0 (#300)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Instruction Following | 1280 | 978 |
Long Context DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 39.5 (#174), Qwen1.5 4b Chat: 30.1 (#290)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Longer Query | 1301 | 988 |
Writing & Preference DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 49.8 (#187), Qwen1.5 4b Chat: 23.8 (#309)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Text | 1294 | 997 |
| LMArena Creative Writing | 1285 | 969 |
| LMArena Multi-Turn | 1297 | 977 |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Qwen1.5 4b Chat?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 28.8 on the Noometry Index.
Is DeepSeek-V2.5 (Sep 2024) or Qwen1.5 4b Chat better for coding?
DeepSeek-V2.5 (Sep 2024) scores higher on coding benchmarks: 31.7 versus 29.1 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Qwen1.5 4b Chat share?
13 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Qwen1.5 4b Chat has 13.