Model comparison
Grok 4.3 vs Qwen3.5 397B-A17B
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 43.8 on the Noometry Index.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. Grok 4.3 scores higher in 1 category and Qwen3.5 397B-A17B in 9 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in multimodal, where Qwen3.5 397B-A17B leads 40.7 to 31.6.
- The biggest single-benchmark swing is Chess Puzzles: 25% for Grok 4.3 and 13% for Qwen3.5 397B-A17B.
- Qwen3.5 397B-A17B is cheaper at $0.60 / $3.60 per million input/output tokens, against $1.25 / $2.50 for Grok 4.3.
- Grok 4.3 accepts more context: 1M tokens versus 262K.
- Qwen3.5 397B-A17B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.3 | Qwen3.5 397B-A17B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 43.8 | 46.0 |
| Released | 2026-04-17 | 2026-02-01 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 30K | 66K |
| Input $ / M tokens | $1.25 | $0.60 |
| Output $ / M tokens | $2.50 | $3.60 |
| Results tracked | 40 | 36 |
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Category by category
Coding Too close to call
Grok 4.3: 41.6 (#121), Qwen3.5 397B-A17B: 42.0 (#114)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena WebDev | 1357 | 1400 |
| LMArena Coding | 1415 | 1465 |
| SciCode | 47.3% | — |
| WeirdML | 49.9% | — |
| ALE-Bench | 944.17 | — |
Agentic & Tool Use Qwen3.5 397B-A17B leads
Grok 4.3: 27.7 (#99), Qwen3.5 397B-A17B: 33.3 (#53)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| APEX-Agents | — | 24.9% |
| τ²-bench Airline | — | 81.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 84.4% |
| τ²-bench Telecom | — | 97.8% |
| GDP.pdf | 8% | — |
| LMArena Search | 1165 | — |
| Vending-Bench 2 | 35.26 | — |
Reasoning Grok 4.3 leads
Grok 4.3: 35.9 (#68), Qwen3.5 397B-A17B: 34.5 (#70)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| NYT Connections (extended) | 55.2% | 58.9% |
| Chess Puzzles | 25% | 13% |
| LMArena Hard Prompts | 1396 | 1448 |
| DTBench | 90.7% | 87.5% |
| LMCA | 38.3% | 37.9% |
| Epoch Capabilities Index | 149.16 | 146.65 |
| Kagi LLM Benchmark | — | 73.7% |
| CritPt | 8% | — |
| Thematic Generalization | — | 65.1% |
| Mystery Game Puzzles | — | 18% |
| ForecastBench | 60.3 | — |
Math Too close to call
Grok 4.3: 46.0 (#74), Qwen3.5 397B-A17B: 46.1 (#73)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 42.8% | 31.2% |
| OTIS Mock AIME 2024-2025 | 93.3% | 88.9% |
| LMArena Math | 1388 | 1454 |
| FrontierMath Tier 4 | 14.6% | — |
| ProofBench | 11% | — |
Knowledge Too close to call
Grok 4.3: 52.5 (#62), Qwen3.5 397B-A17B: 53.3 (#58)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| GPQA Diamond | 88.8% | 86.4% |
| LMArena Expert | 1385 | 1462 |
| SimpleQA Verified | 33.2% | — |
Multimodal Qwen3.5 397B-A17B leads
Grok 4.3: 31.6 (#104), Qwen3.5 397B-A17B: 40.7 (#44)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Vision | 1229 | 1263 |
| Blueprint-Bench 2 | 0% | — |
Multilingual Qwen3.5 397B-A17B leads
Grok 4.3: 50.5 (#120), Qwen3.5 397B-A17B: 53.7 (#59)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Non-English | 1385 | 1430 |
| LMArena Chinese | 1422 | 1500 |
| LMArena French | 1412 | 1461 |
| LMArena German | 1395 | 1447 |
| LMArena Japanese | 1379 | 1426 |
| LMArena Korean | 1356 | 1384 |
| LMArena Russian | 1399 | 1429 |
| LMArena Spanish | 1398 | 1441 |
Instruction Following Qwen3.5 397B-A17B leads
Grok 4.3: 72.1 (#140), Qwen3.5 397B-A17B: 75.0 (#77)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Instruction Following | 1366 | 1424 |
Long Context Qwen3.5 397B-A17B leads
Grok 4.3: 42.5 (#123), Qwen3.5 397B-A17B: 44.1 (#74)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Longer Query | 1393 | 1442 |
Writing & Preference Qwen3.5 397B-A17B leads
Grok 4.3: 58.5 (#118), Qwen3.5 397B-A17B: 62.3 (#79)
| Benchmark | Grok 4.3 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Text | 1397 | 1438 |
| LMArena Creative Writing | 1380 | 1401 |
| LMArena Multi-Turn | 1406 | 1446 |
| EQ-Bench Creative Writing | — | 1478 |
| EQ-Bench 4 | 1075 | — |
Frequently asked questions
Is Grok 4.3 better than Qwen3.5 397B-A17B?
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 43.8 on the Noometry Index.
Which is cheaper, Grok 4.3 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 4.3 lists at $1.25 and $2.50.
Is Grok 4.3 or Qwen3.5 397B-A17B better for coding?
They score almost the same on coding (41.6 vs 42.0); test both on your own repository before choosing.
Which has the bigger context window?
Grok 4.3 does, with 1M tokens against 262K.
How many benchmarks do Grok 4.3 and Qwen3.5 397B-A17B share?
27 benchmarks have published results for both models. Grok 4.3 has 40 scored results on Noometry and Qwen3.5 397B-A17B has 36.