Model comparison
Llama2 70b Steerlm Chat vs Qwen3 8B
Qwen3 8B is the stronger model overall, scoring 33.3 to 31.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
NVIDIA
Alibaba (Qwen)Summary
- The widest gap is in long context, where Qwen3 8B leads 37.8 to 30.4.
Side by side
| Llama2 70b Steerlm Chat | Qwen3 8B | |
|---|---|---|
| Provider | NVIDIA | Alibaba (Qwen) |
| Noometry Index | 31.2 | 33.3 |
| Released | — | 2025-04 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $0.18 |
| Output $ / M tokens | — | $0.70 |
| Results tracked | 9 | 11 |
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Category by category
Coding Qwen3 8B leads
Llama2 70b Steerlm Chat: 29.3 (#295), Qwen3 8B: 33.4 (#245)
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| SciCode | — | 22.6% |
| LMArena Coding | 1025 | — |
Agentic & Tool Use Not comparable
Llama2 70b Steerlm Chat: —, Qwen3 8B: 29.9 (#71)
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 42.6% |
Reasoning Llama2 70b Steerlm Chat leads
Llama2 70b Steerlm Chat: 19.1 (#245), Qwen3 8B: 16.1 (#299)
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| CritPt | — | 0% |
| Chess Puzzles | — | 5% |
| LMArena Hard Prompts | 1047 | — |
| DTBench | — | 59.7% |
| LMCA | — | 8.8% |
| Epoch Capabilities Index | — | 136.17 |
Math Qwen3 8B leads
Llama2 70b Steerlm Chat: 28.8 (#223), Qwen3 8B: 33.3 (#176)
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 56.1% |
| LMArena Math | 1072 | — |
Knowledge Not comparable
Llama2 70b Steerlm Chat: —, Qwen3 8B: 36.1 (#164)
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| GPQA Diamond | — | 56.8% |
| Vectara Hallucination Rate | — | 4.8% |
Multilingual Not comparable
Llama2 70b Steerlm Chat: 28.9 (#265), Qwen3 8B: —
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| LMArena Non-English | 1064 | — |
Instruction Following Not comparable
Llama2 70b Steerlm Chat: 54.5 (#274), Qwen3 8B: —
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| LMArena Instruction Following | 1061 | — |
Long Context Qwen3 8B leads
Llama2 70b Steerlm Chat: 30.4 (#283), Qwen3 8B: 37.8 (#205)
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| Fiction.LiveBench | — | 62.1% |
| LMArena Longer Query | 998 | — |
Writing & Preference Not comparable
Llama2 70b Steerlm Chat: 31.8 (#278), Qwen3 8B: —
| Benchmark | Llama2 70b Steerlm Chat | Qwen3 8B |
|---|---|---|
| LMArena Text | 1098 | — |
| LMArena Creative Writing | 1091 | — |
| LMArena Multi-Turn | 1058 | — |
Frequently asked questions
Is Llama2 70b Steerlm Chat better than Qwen3 8B?
Qwen3 8B is the stronger model overall, scoring 33.3 to 31.2 on the Noometry Index.
Is Llama2 70b Steerlm Chat or Qwen3 8B better for coding?
Qwen3 8B scores higher on coding benchmarks: 33.4 versus 29.3 in the Noometry coding category.
How many benchmarks do Llama2 70b Steerlm Chat and Qwen3 8B share?
0 benchmarks have published results for both models. Llama2 70b Steerlm Chat has 9 scored results on Noometry and Qwen3 8B has 11.