Model comparison
Grok 4.3 vs Qwen3-30B-A3B
Grok 4.3 is the stronger model overall, scoring 43.6 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 7.3× less per token, which makes it the better buy when Grok 4.3's lead doesn't matter for your workload.
Last verified . 26 shared benchmarks.
Alibaba (Qwen)Summary
- They share 26 benchmarks with published results for both. Grok 4.3 scores higher in 8 categories and Qwen3-30B-A3B in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.3 leads 34.9 to 21.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.3% for Grok 4.3 and 70.3% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $1.25 / $2.50 for Grok 4.3.
- Grok 4.3 accepts more context: 1M tokens versus 41K.
- Qwen3-30B-A3B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.3 | Qwen3-30B-A3B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 43.6 | 38.5 |
| Released | 2026-04-17 | 2025-04-28 |
| Weights | Proprietary | Open |
| Context window | 1M | 41K |
| Max output | 30K | 16K |
| Input $ / M tokens | $1.25 | $0.12 |
| Output $ / M tokens | $2.50 | $0.50 |
| Results tracked | 40 | 32 |
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Category by category
Coding Grok 4.3 leads
Grok 4.3: 41.3 (#117), Qwen3-30B-A3B: 37.0 (#188)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| SciCode | 47.3% | 33.3% |
| WeirdML | 49.9% | 29.8% |
| LMArena Coding | 1415 | 1416 |
| LMArena WebDev | 1357 | — |
| ALE-Bench | 944.17 | — |
Agentic & Tool Use Qwen3-30B-A3B leads
Grok 4.3: 27.6 (#93), Qwen3-30B-A3B: 29.5 (#75)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
| GDP.pdf | 8% | — |
| LMArena Search | 1165 | — |
| Vending-Bench 2 | 35.26 | — |
Reasoning Grok 4.3 leads
Grok 4.3: 34.9 (#60), Qwen3-30B-A3B: 21.6 (#193)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| CritPt | 8% | 0.3% |
| Chess Puzzles | 25% | 8% |
| LMArena Hard Prompts | 1397 | 1398 |
| DTBench | 90.7% | 69.3% |
| LMCA | 38.3% | 22.4% |
| Epoch Capabilities Index | 149.13 | 139.63 |
| Kagi LLM Benchmark | — | 54.9% |
| NYT Connections (extended) | 55.2% | — |
| ForecastBench | 60.3 | — |
Math Grok 4.3 leads
Grok 4.3: 45.8 (#60), Qwen3-30B-A3B: 36.0 (#133)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.3% | 70.3% |
| LMArena Math | 1388 | 1394 |
| FrontierMath (Tiers 1-3) | 42.8% | — |
| FrontierMath Tier 4 | 14.6% | — |
| MathArena Final-Answer Competitions | — | 47.8% |
| ProofBench | 11% | — |
Knowledge Grok 4.3 leads
Grok 4.3: 52.5 (#57), Qwen3-30B-A3B: 41.7 (#96)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 88.8% | 70.1% |
| LMArena Expert | 1385 | 1395 |
| SimpleQA Verified | 33.2% | — |
| Confabulations | — | 12.3% |
Multimodal Not comparable
Grok 4.3: 31.6 (#96), Qwen3-30B-A3B: —
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Vision | 1231 | — |
| Blueprint-Bench 2 | 0% | — |
Multilingual Too close to call
Grok 4.3: 50.7 (#114), Qwen3-30B-A3B: 49.8 (#126)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1385 | 1372 |
| LMArena Chinese | 1423 | 1434 |
| LMArena French | 1412 | 1419 |
| LMArena German | 1395 | 1379 |
| LMArena Japanese | 1379 | 1338 |
| LMArena Korean | 1357 | 1333 |
| LMArena Russian | 1399 | 1369 |
| LMArena Spanish | 1402 | 1403 |
Instruction Following Too close to call
Grok 4.3: 72.3 (#135), Qwen3-30B-A3B: 72.2 (#137)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1366 | 1364 |
Long Context Grok 4.3 leads
Grok 4.3: 42.5 (#118), Qwen3-30B-A3B: 31.0 (#278)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1393 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Grok 4.3 leads
Grok 4.3: 58.6 (#112), Qwen3-30B-A3B: 55.9 (#138)
| Benchmark | Grok 4.3 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1397 | 1384 |
| LMArena Creative Writing | 1380 | 1318 |
| LMArena Multi-Turn | 1406 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench 4 | 1075 | — |
Frequently asked questions
Is Grok 4.3 better than Qwen3-30B-A3B?
Grok 4.3 is the stronger model overall, scoring 43.6 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 7.3× less per token, which makes it the better buy when Grok 4.3's lead doesn't matter for your workload.
Which is cheaper, Grok 4.3 or Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; Grok 4.3 lists at $1.25 and $2.50.
Is Grok 4.3 or Qwen3-30B-A3B better for coding?
Grok 4.3 scores higher on coding benchmarks: 41.3 versus 37.0 in the Noometry coding category.
Which has the bigger context window?
Grok 4.3 does, with 1M tokens against 41K.
How many benchmarks do Grok 4.3 and Qwen3-30B-A3B share?
26 benchmarks have published results for both models. Grok 4.3 has 40 scored results on Noometry and Qwen3-30B-A3B has 32.