Model comparison
Grok 4.7 vs Qwen3-Coder 480B-A35B Instruct
Grok 4.7 is the stronger model overall, scoring 53.1 to 38.1 on the Noometry Index.
Last verified . 15 shared benchmarks.
Summary
- They share 15 benchmarks with published results for both. Grok 4.7 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 knowledge, where Grok 4.7 leads 62.8 to 37.0.
- Both cost about the same: $2 input and $6 output per million tokens.
- Grok 4.7 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 4.7 | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 53.1 | 38.1 |
| Released | 2026-09-21 | 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 | 39 | 25 |
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Category by category
Coding Grok 4.7 leads
Grok 4.7: 58.0 (#18), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena WebDev | 1639 | 1275 |
| LMArena Coding | 1427 | 1412 |
| FrontierCode | 47.6% | — |
| SWE-bench Verified (bash only) | — | 55.4% |
| CursorBench | 46.3% | — |
| FrontierSWE | 29.5% | — |
| SciCode | 57.8% | — |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Grok 4.7 leads
Grok 4.7: 36.7 (#37), Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| APEX-Agents | 54.6% | — |
| GDP.pdf | 22.8% | — |
| Vending-Bench 2 | 10,537 | — |
Reasoning Grok 4.7 leads
Grok 4.7: 49.1 (#40), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1413 | 1372 |
| Kagi LLM Benchmark | — | 49.5% |
| NYT Connections (extended) | 76.8% | — |
| CritPt | 18% | — |
| Chess Puzzles | 38% | — |
| Mystery Game Puzzles | 29% | — |
| DTBench | 96% | — |
| LMCA | 49.4% | — |
| Epoch Capabilities Index | 153.53 | — |
Math Grok 4.7 leads
Grok 4.7: 57.8 (#39), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1407 | 1365 |
| FrontierMath (Tiers 1-3) | 53% | — |
| FrontierMath Tier 4 | 17.1% | — |
| OTIS Mock AIME 2024-2025 | 98.1% | — |
| ProofBench | 34% | — |
Knowledge Grok 4.7 leads
Grok 4.7: 62.8 (#22), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1422 | 1338 |
| GPQA Diamond | 92.7% | — |
| SimpleQA Verified | 56% | — |
Multimodal Not comparable
Grok 4.7: 35.5 (#87), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1228 | — |
| Blueprint-Bench 2 | 32.5% | — |
| Furniture Assembly | 20.8% | — |
Multilingual Grok 4.7 leads
Grok 4.7: 50.8 (#116), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1389 | 1346 |
| LMArena Chinese | 1455 | 1357 |
| LMArena French | 1455 | 1398 |
| LMArena Russian | 1397 | 1366 |
| LMArena Spanish | 1400 | 1360 |
| LMArena German | — | 1325 |
| LMArena Japanese | — | 1310 |
| LMArena Korean | — | 1305 |
Instruction Following Grok 4.7 leads
Grok 4.7: 74.1 (#105), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1404 | 1355 |
Long Context Grok 4.7 leads
Grok 4.7: 43.1 (#104), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1413 | 1378 |
Writing & Preference Grok 4.7 leads
Grok 4.7: 70.0 (#24), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | Grok 4.7 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1399 | 1357 |
| LMArena Creative Writing | 1391 | 1333 |
| LMArena Multi-Turn | 1393 | 1365 |
| EQ-Bench Creative Writing | 2007 | — |
Frequently asked questions
Is Grok 4.7 better than Qwen3-Coder 480B-A35B Instruct?
Grok 4.7 is the stronger model overall, scoring 53.1 to 38.1 on the Noometry Index.
Which is cheaper, Grok 4.7 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 4.7 lists at $2 and $6.
Is Grok 4.7 or Qwen3-Coder 480B-A35B Instruct better for coding?
Grok 4.7 scores higher on coding benchmarks: 58.0 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Grok 4.7 does, with 500K tokens against 262K.
How many benchmarks do Grok 4.7 and Qwen3-Coder 480B-A35B Instruct share?
15 benchmarks have published results for both models. Grok 4.7 has 39 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.