Model comparison
Llama 3.1 Tulu 3 8b vs Qwen3-30B-A3B
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 35.7 on the Noometry Index.
Last verified . 11 shared benchmarks.
Allen Institute for AI (Ai2)
Alibaba (Qwen)Summary
- They share 11 benchmarks with published results for both. Llama 3.1 Tulu 3 8b scores higher in 2 categories and Qwen3-30B-A3B in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3-30B-A3B leads 55.6 to 39.7.
Side by side
| Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Allen Institute for AI (Ai2) | Alibaba (Qwen) |
| Noometry Index | 35.7 | 38.9 |
| Released | — | 2025-04-28 |
| Weights | Open | Open |
| Context window | — | 41K |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.12 |
| Output $ / M tokens | — | $0.50 |
| Results tracked | 11 | 32 |
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Category by category
Coding Qwen3-30B-A3B leads
Llama 3.1 Tulu 3 8b: 34.4 (#235), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| LMArena Coding | 1183 | 1416 |
| SciCode | — | 33.3% |
| WeirdML | — | 29.8% |
Agentic & Tool Use Not comparable
Llama 3.1 Tulu 3 8b: —, Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
Reasoning Too close to call
Llama 3.1 Tulu 3 8b: 22.8 (#188), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| LMArena Hard Prompts | 1174 | 1398 |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 8% |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |
| Epoch Capabilities Index | — | 139.63 |
Math Qwen3-30B-A3B leads
Llama 3.1 Tulu 3 8b: 33.9 (#198), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| LMArena Math | 1195 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
| OTIS Mock AIME 2024-2025 | — | 70.3% |
Knowledge Not comparable
Llama 3.1 Tulu 3 8b: —, Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | — | 70.1% |
| Confabulations | — | 12.3% |
| LMArena Expert | — | 1396 |
Multilingual Qwen3-30B-A3B leads
Llama 3.1 Tulu 3 8b: 35.4 (#246), Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1169 | 1372 |
| LMArena Chinese | 1176 | 1433 |
| LMArena Russian | 1193 | 1370 |
| LMArena French | — | 1418 |
| LMArena German | — | 1380 |
| LMArena Japanese | — | 1337 |
| LMArena Korean | — | 1331 |
| LMArena Spanish | — | 1404 |
Instruction Following Qwen3-30B-A3B leads
Llama 3.1 Tulu 3 8b: 61.3 (#246), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1174 | 1363 |
Long Context Llama 3.1 Tulu 3 8b leads
Llama 3.1 Tulu 3 8b: 35.8 (#239), Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1181 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Qwen3-30B-A3B leads
Llama 3.1 Tulu 3 8b: 39.7 (#245), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | Llama 3.1 Tulu 3 8b | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1193 | 1384 |
| LMArena Creative Writing | 1182 | 1317 |
| LMArena Multi-Turn | 1154 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
Frequently asked questions
Is Llama 3.1 Tulu 3 8b better than Qwen3-30B-A3B?
Qwen3-30B-A3B is the stronger model overall, scoring 38.9 to 35.7 on the Noometry Index.
Is Llama 3.1 Tulu 3 8b or Qwen3-30B-A3B better for coding?
Qwen3-30B-A3B scores higher on coding benchmarks: 37.5 versus 34.4 in the Noometry coding category.
How many benchmarks do Llama 3.1 Tulu 3 8b and Qwen3-30B-A3B share?
11 benchmarks have published results for both models. Llama 3.1 Tulu 3 8b has 11 scored results on Noometry and Qwen3-30B-A3B has 32.