Model comparison
Grok 4.6 vs Qwen3-Coder 480B-A35B Instruct
Grok 4.6 is the stronger model overall, scoring 56.9 to 38.1 on the Noometry Index.
Last verified . 20 shared benchmarks.
Alibaba (Qwen)Summary
- They share 20 benchmarks with published results for both. Grok 4.6 scores higher in 9 categories and Qwen3-Coder 480B-A35B Instruct in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.6 leads 61.4 to 25.5.
- The biggest single-benchmark swing is WeirdML: 67.3% for Grok 4.6 and 41.2% for Qwen3-Coder 480B-A35B Instruct.
- Both cost about the same: $2 input and $6 output per million tokens.
- Grok 4.6 accepts more context: 500K tokens versus 262K.
- Qwen3-Coder 480B-A35B Instruct has downloadable open weights; the other is API-only.
Side by side
| Grok 4.6 | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 56.9 | 38.1 |
| Released | 2026-08-12 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 500K | 262K |
| Max output | 500K | 66K |
| Input $ / M tokens | $2 | $1.50 |
| Output $ / M tokens | $6 | $7.50 |
| Results tracked | 49 | 25 |
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Category by category
Coding Grok 4.6 leads
Grok 4.6: 58.5 (#16), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena WebDev | 1617 | 1275 |
| WeirdML | 67.3% | 41.2% |
| LMArena Coding | 1465 | 1412 |
| ALE-Bench | 1,508 | 461.45 |
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| SWE-bench Verified (bash only) | — | 55.4% |
| CursorBench | 41.4% | — |
| FrontierSWE | 25.3% | — |
| SciCode | 56.5% | — |
| GSO | — | 4.9% |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Grok 4.6 leads
Grok 4.6: 39.4 (#27), Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| APEX-Agents | 65.3% | — |
| GDP.pdf | 17.2% | — |
| Vending-Bench 2 | 9,047 | — |
Reasoning Grok 4.6 leads
Grok 4.6: 61.4 (#20), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1447 | 1372 |
| ARC-AGI-2 | 67.1% | — |
| SimpleBench | 75.9% | — |
| Kagi LLM Benchmark | — | 49.5% |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| CritPt | 19.7% | — |
| Chess Puzzles | 40% | — |
| EBR-Bench | 30.5% | — |
| 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-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1423 | 1365 |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 31.7% | — |
| OTIS Mock AIME 2024-2025 | 99.2% | — |
| ProofBench | 51% | — |
Knowledge Grok 4.6 leads
Grok 4.6: 63.3 (#20), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1467 | 1338 |
| GPQA Diamond | 94% | — |
| SimpleQA Verified | 49.3% | — |
Multimodal Not comparable
Grok 4.6: 43.6 (#23), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |
Multilingual Grok 4.6 leads
Grok 4.6: 53.0 (#74), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1420 | 1346 |
| LMArena Chinese | 1480 | 1357 |
| LMArena French | 1461 | 1398 |
| LMArena German | 1431 | 1325 |
| LMArena Japanese | 1376 | 1310 |
| LMArena Korean | 1397 | 1305 |
| LMArena Russian | 1422 | 1366 |
| LMArena Spanish | 1404 | 1360 |
Instruction Following Grok 4.6 leads
Grok 4.6: 75.4 (#63), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1431 | 1355 |
Long Context Grok 4.6 leads
Grok 4.6: 44.5 (#66), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1454 | 1378 |
Writing & Preference Grok 4.6 leads
Grok 4.6: 62.3 (#80), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | Grok 4.6 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1428 | 1357 |
| LMArena Creative Writing | 1428 | 1333 |
| LMArena Multi-Turn | 1425 | 1365 |
Frequently asked questions
Is Grok 4.6 better than Qwen3-Coder 480B-A35B Instruct?
Grok 4.6 is the stronger model overall, scoring 56.9 to 38.1 on the Noometry Index.
Which is cheaper, Grok 4.6 or Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; Grok 4.6 lists at $2 and $6.
Is Grok 4.6 or Qwen3-Coder 480B-A35B Instruct better for coding?
Grok 4.6 scores higher on coding benchmarks: 58.5 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Grok 4.6 does, with 500K tokens against 262K.
How many benchmarks do Grok 4.6 and Qwen3-Coder 480B-A35B Instruct share?
20 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.