Model comparison
Qwen2.5 7B Instruct vs Wizardlm 13b
Wizardlm 13b is the stronger model overall, scoring 31.4 to 29.0 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)
MicrosoftSummary
- The widest gap is in writing & preference, where Qwen2.5 7B Instruct leads 48.8 to 30.5.
Side by side
| Qwen2.5 7B Instruct | Wizardlm 13b | |
|---|---|---|
| Provider | Alibaba (Qwen) | Microsoft |
| Noometry Index | 29.0 | 31.4 |
| Released | 2024-09 | — |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.17 | — |
| Output $ / M tokens | $0.70 | — |
| Results tracked | 15 | 10 |
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Category by category
Coding Qwen2.5 7B Instruct leads
Qwen2.5 7B Instruct: 36.5 (#208), Wizardlm 13b: 30.1 (#298)
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| BigCodeBench Instruct | 37.6% | — |
| LMArena Coding | — | 1035 |
| BigCodeBench Complete | 46.1% | — |
Agentic & Tool Use Not comparable
Qwen2.5 7B Instruct: 23.8 (#124), Wizardlm 13b: —
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| BALROG | 7.8% | — |
Reasoning Wizardlm 13b leads
Qwen2.5 7B Instruct: 14.8 (#322), Wizardlm 13b: 19.4 (#259)
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | — | 1018 |
| DTBench | 47.7% | — |
| LMCA | 6.4% | — |
| Epoch Capabilities Index | 118.51 | — |
Math Wizardlm 13b leads
Qwen2.5 7B Instruct: 12.6 (#306), Wizardlm 13b: 30.2 (#238)
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 2.5% | — |
| Omni-MATH | 29.4% | — |
| LMArena Math | — | 1017 |
Knowledge Not comparable
Qwen2.5 7B Instruct: 17.0 (#286), Wizardlm 13b: —
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| GPQA Diamond | 35.5% | — |
| MMLU-Pro | 53.9% | — |
| GPQA (HELM) | 34.1% | — |
| MMLU | 72.9% | — |
Multilingual Not comparable
Qwen2.5 7B Instruct: —, Wizardlm 13b: 27.1 (#277)
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| LMArena Non-English | — | 1034 |
| LMArena Chinese | — | 1023 |
Instruction Following Qwen2.5 7B Instruct leads
Qwen2.5 7B Instruct: 63.2 (#231), Wizardlm 13b: 53.5 (#285)
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| IFEval | 74.1% | — |
| LMArena Instruction Following | — | 1048 |
Long Context Not comparable
Qwen2.5 7B Instruct: —, Wizardlm 13b: 32.0 (#273)
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| LMArena Longer Query | — | 1054 |
Writing & Preference Qwen2.5 7B Instruct leads
Qwen2.5 7B Instruct: 48.8 (#195), Wizardlm 13b: 30.5 (#287)
| Benchmark | Qwen2.5 7B Instruct | Wizardlm 13b |
|---|---|---|
| LMArena Text | — | 1077 |
| LMArena Creative Writing | — | 1091 |
| WildBench | 73.1% | — |
| LMArena Multi-Turn | — | 1047 |
Frequently asked questions
Is Qwen2.5 7B Instruct better than Wizardlm 13b?
Wizardlm 13b is the stronger model overall, scoring 31.4 to 29.0 on the Noometry Index.
Is Qwen2.5 7B Instruct or Wizardlm 13b better for coding?
Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 30.1 in the Noometry coding category.
How many benchmarks do Qwen2.5 7B Instruct and Wizardlm 13b share?
0 benchmarks have published results for both models. Qwen2.5 7B Instruct has 15 scored results on Noometry and Wizardlm 13b has 10.