Model comparison
Grok 4.6 vs Qwen3-1.7B
Grok 4.6 is the stronger model overall, scoring 56.9 to 26.6 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Grok 4.6 scores higher in 4 categories and Qwen3-1.7B in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Grok 4.6 leads 67.0 to 16.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 99.2% for Grok 4.6 and 8.1% for Qwen3-1.7B.
- Qwen3-1.7B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.6 | Qwen3-1.7B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 56.9 | 26.6 |
| Released | 2026-08-12 | 2025-04-29 |
| Weights | Proprietary | Open |
| Context window | 500K | — |
| Max output | 500K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $6 | — |
| Results tracked | 49 | 4 |
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Category by category
Coding Not comparable
Grok 4.6: 58.5 (#16), Qwen3-1.7B: —
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| CursorBench | 41.4% | — |
| LMArena WebDev | 1617 | — |
| FrontierSWE | 25.3% | — |
| SciCode | 56.5% | — |
| WeirdML | 67.3% | — |
| LMArena Coding | 1465 | — |
| ALE-Bench | 1,508 | — |
Agentic & Tool Use Grok 4.6 leads
Grok 4.6: 39.4 (#27), Qwen3-1.7B: 24.7 (#115)
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| APEX-Agents | 65.3% | — |
| Berkeley Function Calling Leaderboard | — | 28.4% |
| GDP.pdf | 17.2% | — |
| Vending-Bench 2 | 9,047 | — |
Reasoning Grok 4.6 leads
Grok 4.6: 61.4 (#20), Qwen3-1.7B: 19.2 (#267)
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| Chess Puzzles | 40% | 0% |
| ARC-AGI-2 | 67.1% | — |
| SimpleBench | 75.9% | — |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| CritPt | 19.7% | — |
| EBR-Bench | 30.5% | — |
| LMArena Hard Prompts | 1447 | — |
| Mystery Game Puzzles | 34% | — |
| DTBench | 97.3% | — |
| LMCA | 48.5% | — |
| Epoch Capabilities Index | 156.44 | — |
Math Grok 4.6 leads
Grok 4.6: 67.0 (#24), Qwen3-1.7B: 16.3 (#294)
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 99.2% | 8.1% |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 31.7% | — |
| ProofBench | 51% | — |
| LMArena Math | 1423 | — |
Knowledge Grok 4.6 leads
Grok 4.6: 63.3 (#20), Qwen3-1.7B: 19.6 (#278)
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 94% | 38% |
| SimpleQA Verified | 49.3% | — |
| LMArena Expert | 1467 | — |
Multimodal Not comparable
Grok 4.6: 43.6 (#23), Qwen3-1.7B: —
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |
Multilingual Not comparable
Grok 4.6: 53.0 (#74), Qwen3-1.7B: —
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1420 | — |
| LMArena Chinese | 1480 | — |
| LMArena French | 1461 | — |
| LMArena German | 1431 | — |
| LMArena Japanese | 1376 | — |
| LMArena Korean | 1397 | — |
| LMArena Russian | 1422 | — |
| LMArena Spanish | 1404 | — |
Instruction Following Not comparable
Grok 4.6: 75.4 (#63), Qwen3-1.7B: —
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1431 | — |
Long Context Not comparable
Grok 4.6: 44.5 (#66), Qwen3-1.7B: —
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1454 | — |
Writing & Preference Not comparable
Grok 4.6: 62.3 (#80), Qwen3-1.7B: —
| Benchmark | Grok 4.6 | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1428 | — |
| LMArena Creative Writing | 1428 | — |
| LMArena Multi-Turn | 1425 | — |
Frequently asked questions
Is Grok 4.6 better than Qwen3-1.7B?
Grok 4.6 is the stronger model overall, scoring 56.9 to 26.6 on the Noometry Index.
How many benchmarks do Grok 4.6 and Qwen3-1.7B share?
3 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Qwen3-1.7B has 4.