Model comparison
Grok 4.3 vs Qwen3 235B-A22B
Grok 4.3 and Qwen3 235B-A22B score almost the same on the Noometry Index (43.6 vs 43.2), so choose on price, context window or the category you care about most.
Last verified . 29 shared benchmarks.
Alibaba (Qwen)Summary
- They share 29 benchmarks with published results for both. Grok 4.3 scores higher in 2 categories and Qwen3 235B-A22B in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.3 leads 34.9 to 15.8.
- The biggest single-benchmark swing is Chess Puzzles: 25% for Grok 4.3 and 12% for Qwen3 235B-A22B.
- Qwen3 235B-A22B is cheaper at $0.70 / $2.80 per million input/output tokens, against $1.25 / $2.50 for Grok 4.3.
- Grok 4.3 accepts more context: 1M tokens versus 131K.
- Qwen3 235B-A22B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.3 | Qwen3 235B-A22B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 43.6 | 43.2 |
| Released | 2026-04-17 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 30K | 16K |
| Input $ / M tokens | $1.25 | $0.70 |
| Output $ / M tokens | $2.50 | $2.80 |
| Results tracked | 40 | 49 |
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Category by category
Coding Qwen3 235B-A22B leads
Grok 4.3: 41.3 (#117), Qwen3 235B-A22B: 43.8 (#72)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| SciCode | 47.3% | 42.4% |
| WeirdML | 49.9% | 41% |
| LMArena Coding | 1415 | 1445 |
| Aider Polyglot | — | 59.6% |
| LMArena WebDev | 1357 | — |
| ALE-Bench | 944.17 | — |
Agentic & Tool Use Qwen3 235B-A22B leads
Grok 4.3: 27.6 (#93), Qwen3 235B-A22B: 33.7 (#48)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| Vending-Bench 2 | 35.26 | -11.34 |
| Berkeley Function Calling Leaderboard | — | 52.1% |
| GDP.pdf | 8% | — |
| LMArena Search | 1165 | — |
Reasoning Grok 4.3 leads
Grok 4.3: 34.9 (#60), Qwen3 235B-A22B: 15.8 (#302)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| CritPt | 8% | 0% |
| Chess Puzzles | 25% | 12% |
| LMArena Hard Prompts | 1397 | 1433 |
| DTBench | 90.7% | 80.3% |
| LMCA | 38.3% | 29.3% |
| Epoch Capabilities Index | 149.13 | 143.87 |
| ForecastBench | 60.3 | 59.7 |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31% |
| Kagi LLM Benchmark | — | 69.4% |
| NYT Connections (extended) | 55.2% | — |
| ARC-AGI-1 | — | 11% |
| Mystery Game Puzzles | — | 9% |
Math Qwen3 235B-A22B leads
Grok 4.3: 45.8 (#60), Qwen3 235B-A22B: 48.5 (#51)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.3% | 86.7% |
| LMArena Math | 1388 | 1431 |
| FrontierMath (Tiers 1-3) | 42.8% | — |
| FrontierMath Tier 4 | 14.6% | — |
| ProofBench | 11% | — |
| Omni-MATH | — | 71.8% |
| MATH Level 5 | — | 68.9% |
| FrontierMath (Feb 2025 set) | — | 8.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Grok 4.3 leads
Grok 4.3: 52.5 (#57), Qwen3 235B-A22B: 49.5 (#67)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| GPQA Diamond | 88.8% | 80.1% |
| SimpleQA Verified | 33.2% | 40.4% |
| LMArena Expert | 1385 | 1460 |
| MMLU-Pro | — | 84.4% |
| Confabulations | — | 15.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 72.7% |
Multimodal Not comparable
Grok 4.3: 31.6 (#96), Qwen3 235B-A22B: —
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Vision | 1231 | — |
| Blueprint-Bench 2 | 0% | — |
Multilingual Qwen3 235B-A22B leads
Grok 4.3: 50.7 (#114), Qwen3 235B-A22B: 52.5 (#84)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | 1385 | 1410 |
| LMArena Chinese | 1423 | 1481 |
| LMArena French | 1412 | 1445 |
| LMArena German | 1395 | 1432 |
| LMArena Japanese | 1379 | 1400 |
| LMArena Korean | 1357 | 1391 |
| LMArena Russian | 1399 | 1411 |
| LMArena Spanish | 1402 | 1429 |
Instruction Following Too close to call
Grok 4.3: 72.3 (#135), Qwen3 235B-A22B: 72.8 (#132)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1366 | 1408 |
| IFEval | — | 83.5% |
Long Context Qwen3 235B-A22B leads
Grok 4.3: 42.5 (#118), Qwen3 235B-A22B: 46.1 (#25)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Longer Query | 1393 | 1426 |
| Fiction.LiveBench | — | 75% |
Writing & Preference Qwen3 235B-A22B leads
Grok 4.3: 58.6 (#112), Qwen3 235B-A22B: 59.8 (#103)
| Benchmark | Grok 4.3 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | 1397 | 1419 |
| LMArena Creative Writing | 1380 | 1384 |
| LMArena Multi-Turn | 1406 | 1432 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1366 |
| WildBench | — | 86.6% |
| EQ-Bench 4 | 1075 | — |
Frequently asked questions
Is Grok 4.3 better than Qwen3 235B-A22B?
Grok 4.3 and Qwen3 235B-A22B score almost the same on the Noometry Index (43.6 vs 43.2), so choose on price, context window or the category you care about most.
Which is cheaper, Grok 4.3 or Qwen3 235B-A22B?
Qwen3 235B-A22B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Grok 4.3 lists at $1.25 and $2.50.
Is Grok 4.3 or Qwen3 235B-A22B better for coding?
Qwen3 235B-A22B scores higher on coding benchmarks: 43.8 versus 41.3 in the Noometry coding category.
Which has the bigger context window?
Grok 4.3 does, with 1M tokens against 131K.
How many benchmarks do Grok 4.3 and Qwen3 235B-A22B share?
29 benchmarks have published results for both models. Grok 4.3 has 40 scored results on Noometry and Qwen3 235B-A22B has 49.