Model comparison
Grok-2 (Dec 2024) vs Qwen3-1.7B
Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 26.6 on the Noometry Index.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Grok-2 (Dec 2024) scores higher in 2 categories and Qwen3-1.7B in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Grok-2 (Dec 2024) leads 29.8 to 19.6.
- The biggest single-benchmark swing is GPQA Diamond: 53.8% for Grok-2 (Dec 2024) and 38% for Qwen3-1.7B.
- Qwen3-1.7B has downloadable open weights; the other is API-only.
Side by side
| Grok-2 (Dec 2024) | Qwen3-1.7B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 33.7 | 26.6 |
| Released | 2024-08-13 | 2025-04-29 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 34 | 4 |
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Category by category
Coding Not comparable
Grok-2 (Dec 2024): 33.3 (#258), Qwen3-1.7B: —
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| WeirdML | 22.2% | — |
| LiveBench Coding | 46.4% | — |
| LMArena Coding | 1287 | — |
Agentic & Tool Use Not comparable
Grok-2 (Dec 2024): —, Qwen3-1.7B: 24.7 (#115)
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
Reasoning Qwen3-1.7B leads
Grok-2 (Dec 2024): 16.9 (#299), Qwen3-1.7B: 19.2 (#267)
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| SimpleBench | 22.7% | — |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | 54.8% | — |
| LMArena Hard Prompts | 1272 | — |
| DTBench | 65.2% | — |
| LiveBench Data Analysis | 54.5% | — |
| Epoch Capabilities Index | 130.48 | — |
| LiveBench | 54.3% | — |
Math Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 20.8 (#284), Qwen3-1.7B: 16.3 (#294)
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 11.5% | 8.1% |
| LiveBench Math | 54.9% | — |
| LMArena Math | 1283 | — |
| MATH Level 5 | 63.5% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |
Knowledge Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 29.8 (#233), Qwen3-1.7B: 19.6 (#278)
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 53.8% | 38% |
| Confabulations | 20.1% | — |
| LMArena Expert | 1254 | — |
Multilingual Not comparable
Grok-2 (Dec 2024): 43.1 (#188), Qwen3-1.7B: —
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1282 | — |
| LMArena Chinese | 1289 | — |
| LMArena French | 1318 | — |
| LMArena German | 1287 | — |
| LMArena Japanese | 1244 | — |
| LMArena Korean | 1237 | — |
| LMArena Russian | 1286 | — |
| LMArena Spanish | 1281 | — |
Instruction Following Not comparable
Grok-2 (Dec 2024): 66.9 (#202), Qwen3-1.7B: —
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| LiveBench Instruction Following | 69.6% | — |
| LMArena Instruction Following | 1270 | — |
Long Context Not comparable
Grok-2 (Dec 2024): 38.8 (#190), Qwen3-1.7B: —
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1276 | — |
Writing & Preference Not comparable
Grok-2 (Dec 2024): 48.6 (#198), Qwen3-1.7B: —
| Benchmark | Grok-2 (Dec 2024) | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1305 | — |
| LMArena Creative Writing | 1284 | — |
| Short-Story Creative Writing | 63.6% | — |
| LMArena Multi-Turn | 1290 | — |
| LiveBench Language | 45.6% | — |
Frequently asked questions
Is Grok-2 (Dec 2024) better than Qwen3-1.7B?
Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 26.6 on the Noometry Index.
How many benchmarks do Grok-2 (Dec 2024) and Qwen3-1.7B share?
2 benchmarks have published results for both models. Grok-2 (Dec 2024) has 34 scored results on Noometry and Qwen3-1.7B has 4.