Model comparison
Grok 4.7 vs Qwen3.5 397B-A17B
Grok 4.7 is the stronger model overall, scoring 53.1 to 46.0 on the Noometry Index. Qwen3.5 397B-A17B costs 2.2× less per token, which makes it the better buy when Grok 4.7's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Alibaba (Qwen)Summary
- They share 27 benchmarks with published results for both. Grok 4.7 scores higher in 6 categories and Qwen3.5 397B-A17B in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where Grok 4.7 leads 58.0 to 42.0.
- The biggest single-benchmark swing is APEX-Agents: 54.6% for Grok 4.7 and 24.9% for Qwen3.5 397B-A17B.
- Qwen3.5 397B-A17B is cheaper at $0.60 / $3.60 per million input/output tokens, against $2 / $6 for Grok 4.7.
- Grok 4.7 accepts more context: 500K tokens versus 262K.
- Qwen3.5 397B-A17B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.7 | Qwen3.5 397B-A17B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 53.1 | 46.0 |
| Released | 2026-09-21 | 2026-02-01 |
| Weights | Proprietary | Open |
| Context window | 500K | 262K |
| Max output | 500K | 66K |
| Input $ / M tokens | $2 | $0.60 |
| Output $ / M tokens | $6 | $3.60 |
| Results tracked | 39 | 36 |
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Category by category
Coding Grok 4.7 leads
Grok 4.7: 58.0 (#18), Qwen3.5 397B-A17B: 42.0 (#114)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena WebDev | 1639 | 1400 |
| LMArena Coding | 1427 | 1465 |
| FrontierCode | 47.6% | — |
| CursorBench | 46.3% | — |
| FrontierSWE | 29.5% | — |
| SciCode | 57.8% | — |
Agentic & Tool Use Grok 4.7 leads
Grok 4.7: 36.7 (#37), Qwen3.5 397B-A17B: 33.3 (#53)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| APEX-Agents | 54.6% | 24.9% |
| τ²-bench Airline | — | 81.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 84.4% |
| τ²-bench Telecom | — | 97.8% |
| GDP.pdf | 22.8% | — |
| Vending-Bench 2 | 10,537 | — |
Reasoning Grok 4.7 leads
Grok 4.7: 49.1 (#40), Qwen3.5 397B-A17B: 34.5 (#70)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| NYT Connections (extended) | 76.8% | 58.9% |
| Chess Puzzles | 38% | 13% |
| LMArena Hard Prompts | 1413 | 1448 |
| Mystery Game Puzzles | 29% | 18% |
| DTBench | 96% | 87.5% |
| LMCA | 49.4% | 37.9% |
| Epoch Capabilities Index | 153.53 | 146.65 |
| Kagi LLM Benchmark | — | 73.7% |
| CritPt | 18% | — |
| Thematic Generalization | — | 65.1% |
Math Grok 4.7 leads
Grok 4.7: 57.8 (#39), Qwen3.5 397B-A17B: 46.1 (#73)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 53% | 31.2% |
| OTIS Mock AIME 2024-2025 | 98.1% | 88.9% |
| LMArena Math | 1407 | 1454 |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 34% | — |
Knowledge Grok 4.7 leads
Grok 4.7: 62.8 (#22), Qwen3.5 397B-A17B: 53.3 (#58)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| GPQA Diamond | 92.7% | 86.4% |
| LMArena Expert | 1422 | 1462 |
| SimpleQA Verified | 56% | — |
Multimodal Qwen3.5 397B-A17B leads
Grok 4.7: 35.5 (#87), Qwen3.5 397B-A17B: 40.7 (#44)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Vision | 1228 | 1263 |
| Blueprint-Bench 2 | 32.5% | — |
| Furniture Assembly | 20.8% | — |
Multilingual Qwen3.5 397B-A17B leads
Grok 4.7: 50.8 (#116), Qwen3.5 397B-A17B: 53.7 (#59)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Non-English | 1389 | 1430 |
| LMArena Chinese | 1455 | 1500 |
| LMArena French | 1455 | 1461 |
| LMArena Russian | 1397 | 1429 |
| LMArena Spanish | 1400 | 1441 |
| LMArena German | — | 1447 |
| LMArena Japanese | — | 1426 |
| LMArena Korean | — | 1384 |
Instruction Following Too close to call
Grok 4.7: 74.1 (#105), Qwen3.5 397B-A17B: 75.0 (#77)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1424 |
Long Context Too close to call
Grok 4.7: 43.1 (#104), Qwen3.5 397B-A17B: 44.1 (#74)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Longer Query | 1413 | 1442 |
Writing & Preference Grok 4.7 leads
Grok 4.7: 70.0 (#24), Qwen3.5 397B-A17B: 62.3 (#79)
| Benchmark | Grok 4.7 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Text | 1399 | 1438 |
| LMArena Creative Writing | 1391 | 1401 |
| EQ-Bench Creative Writing | 2007 | 1478 |
| LMArena Multi-Turn | 1393 | 1446 |
Frequently asked questions
Is Grok 4.7 better than Qwen3.5 397B-A17B?
Grok 4.7 is the stronger model overall, scoring 53.1 to 46.0 on the Noometry Index. Qwen3.5 397B-A17B costs 2.2× less per token, which makes it the better buy when Grok 4.7's lead doesn't matter for your workload.
Which is cheaper, Grok 4.7 or Qwen3.5 397B-A17B?
Qwen3.5 397B-A17B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; Grok 4.7 lists at $2 and $6.
Is Grok 4.7 or Qwen3.5 397B-A17B better for coding?
Grok 4.7 scores higher on coding benchmarks: 58.0 versus 42.0 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 Qwen3.5 397B-A17B share?
27 benchmarks have published results for both models. Grok 4.7 has 39 scored results on Noometry and Qwen3.5 397B-A17B has 36.