Model comparison
Llama-3.3-70B-Instruct vs Qwen3-1.7B
Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 26.6 on the Noometry Index.
Last verified . 3 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 2 categories and Qwen3-1.7B in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama-3.3-70B-Instruct leads 30.6 to 19.6.
- The biggest single-benchmark swing is GPQA Diamond: 47.4% for Llama-3.3-70B-Instruct and 38% for Qwen3-1.7B.
Side by side
| Llama-3.3-70B-Instruct | Qwen3-1.7B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.6 | 26.6 |
| Released | 2024-12-06 | 2025-04-29 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.10 | — |
| Output $ / M tokens | $0.32 | — |
| Results tracked | 43 | 4 |
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Category by category
Coding Not comparable
Llama-3.3-70B-Instruct: 31.0 (#290), Qwen3-1.7B: —
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| SciCode | 26% | — |
| WeirdML | 14.4% | — |
| BigCodeBench Instruct | 46.9% | — |
| LiveBench Coding | 36.6% | — |
| LMArena Coding | 1268 | — |
| BigCodeBench Complete | 57.5% | — |
Agentic & Tool Use Llama-3.3-70B-Instruct leads
Llama-3.3-70B-Instruct: 25.8 (#105), Qwen3-1.7B: 24.7 (#115)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | 28.4% |
| BALROG | 23% | — |
Reasoning Qwen3-1.7B leads
Llama-3.3-70B-Instruct: 14.1 (#327), Qwen3-1.7B: 19.2 (#267)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| SimpleBench | 19.9% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | 50.8% | — |
| LMArena Hard Prompts | 1257 | — |
| DTBench | 59.5% | — |
| LiveBench Data Analysis | 49.5% | — |
| LMCA | 17.5% | — |
| Epoch Capabilities Index | 127.33 | — |
| ForecastBench | 58.6 | — |
| LiveBench | 50.2% | — |
Math Qwen3-1.7B leads
Llama-3.3-70B-Instruct: 15.3 (#298), Qwen3-1.7B: 16.3 (#294)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | 8.1% |
| LiveBench Math | 42.2% | — |
| LMArena Math | 1267 | — |
| MATH Level 5 | 41.6% | — |
Knowledge Llama-3.3-70B-Instruct leads
Llama-3.3-70B-Instruct: 30.6 (#226), Qwen3-1.7B: 19.6 (#278)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 47.4% | 38% |
| Confabulations | 22.8% | — |
| Vectara Hallucination Rate | 4.1% | — |
| LMArena Expert | 1225 | — |
| MMLU | 86.3% | — |
Multilingual Not comparable
Llama-3.3-70B-Instruct: 39.9 (#220), Qwen3-1.7B: —
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1236 | — |
| LMArena Chinese | 1217 | — |
| LMArena French | 1281 | — |
| LMArena German | 1251 | — |
| LMArena Japanese | 1150 | — |
| LMArena Korean | 1143 | — |
| LMArena Russian | 1252 | — |
| LMArena Spanish | 1270 | — |
Instruction Following Not comparable
Llama-3.3-70B-Instruct: 71.1 (#157), Qwen3-1.7B: —
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| LiveBench Instruction Following | 82.7% | — |
| LMArena Instruction Following | 1242 | — |
Long Context Not comparable
Llama-3.3-70B-Instruct: 26.4 (#295), Qwen3-1.7B: —
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| Fiction.LiveBench | 33.3% | — |
| LMArena Longer Query | 1256 | — |
Writing & Preference Not comparable
Llama-3.3-70B-Instruct: 47.6 (#207), Qwen3-1.7B: —
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1274 | — |
| LMArena Creative Writing | 1250 | — |
| LMArena Multi-Turn | 1280 | — |
| LiveBench Language | 39.2% | — |
Frequently asked questions
Is Llama-3.3-70B-Instruct better than Qwen3-1.7B?
Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 26.6 on the Noometry Index.
How many benchmarks do Llama-3.3-70B-Instruct and Qwen3-1.7B share?
3 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Qwen3-1.7B has 4.