Model comparison
Grok 4.7 vs Qwen3-30B-A3B
Grok 4.7 is the stronger model overall, scoring 46.6 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 14× less per token, which makes it the better buy when Grok 4.7's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
Alibaba (Qwen)Summary
- They share 14 benchmarks with published results for both. Grok 4.7 scores higher in 7 categories and Qwen3-30B-A3B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.7 leads 40.1 to 21.6.
- The biggest single-benchmark swing is SciCode: 57.4% for Grok 4.7 and 33.3% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $2 / $6 for Grok 4.7.
- Grok 4.7 accepts more context: 500K tokens versus 41K.
- Qwen3-30B-A3B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.7 | Qwen3-30B-A3B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 46.6 | 38.5 |
| Released | 2026-09-21 | 2025-04-28 |
| Weights | Proprietary | Open |
| Context window | 500K | 41K |
| Max output | 500K | 16K |
| Input $ / M tokens | $2 | $0.12 |
| Output $ / M tokens | $6 | $0.50 |
| Results tracked | 21 | 32 |
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Category by category
Coding Grok 4.7 leads
Grok 4.7: 55.0 (#23), Qwen3-30B-A3B: 37.0 (#188)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| SciCode | 57.4% | 33.3% |
| LMArena Coding | 1423 | 1416 |
| CursorBench | 46.3% | — |
| LMArena WebDev | 1636 | — |
| FrontierSWE | 29.5% | — |
| WeirdML | — | 29.8% |
Agentic & Tool Use Not comparable
Grok 4.7: —, Qwen3-30B-A3B: 29.5 (#75)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
Reasoning Grok 4.7 leads
Grok 4.7: 40.1 (#49), Qwen3-30B-A3B: 21.6 (#193)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| CritPt | 17.7% | 0.3% |
| LMArena Hard Prompts | 1409 | 1398 |
| Kagi LLM Benchmark | — | 54.9% |
| NYT Connections (extended) | 76.8% | — |
| Chess Puzzles | — | 8% |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |
| Epoch Capabilities Index | — | 139.63 |
Math Grok 4.7 leads
Grok 4.7: 41.1 (#73), Qwen3-30B-A3B: 36.0 (#133)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Math | 1393 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
| OTIS Mock AIME 2024-2025 | — | 70.3% |
| ProofBench | 34% | — |
Knowledge Qwen3-30B-A3B leads
Grok 4.7: 38.7 (#130), Qwen3-30B-A3B: 41.7 (#96)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Expert | 1413 | 1395 |
| GPQA Diamond | — | 70.1% |
| Confabulations | — | 12.3% |
Multimodal Not comparable
Grok 4.7: 28.8 (#107), Qwen3-30B-A3B: —
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| Furniture Assembly | 20.8% | — |
Multilingual Grok 4.7 leads
Grok 4.7: 51.2 (#108), Qwen3-30B-A3B: 49.8 (#126)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1392 | 1372 |
| LMArena Chinese | 1476 | 1434 |
| LMArena Russian | 1396 | 1369 |
| LMArena French | — | 1419 |
| LMArena German | — | 1379 |
| LMArena Japanese | — | 1338 |
| LMArena Korean | — | 1333 |
| LMArena Spanish | — | 1403 |
Instruction Following Grok 4.7 leads
Grok 4.7: 74.3 (#98), Qwen3-30B-A3B: 72.2 (#137)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1406 | 1364 |
Long Context Grok 4.7 leads
Grok 4.7: 43.2 (#97), Qwen3-30B-A3B: 31.0 (#278)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1416 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Grok 4.7 leads
Grok 4.7: 70.1 (#23), Qwen3-30B-A3B: 55.9 (#138)
| Benchmark | Grok 4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1397 | 1384 |
| LMArena Creative Writing | 1391 | 1318 |
| LMArena Multi-Turn | 1389 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench Creative Writing | 2007 | — |
Frequently asked questions
Is Grok 4.7 better than Qwen3-30B-A3B?
Grok 4.7 is the stronger model overall, scoring 46.6 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 14× 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 Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; Grok 4.7 lists at $2 and $6.
Is Grok 4.7 or Qwen3-30B-A3B better for coding?
Grok 4.7 scores higher on coding benchmarks: 55.0 versus 37.0 in the Noometry coding category.
Which has the bigger context window?
Grok 4.7 does, with 500K tokens against 41K.
How many benchmarks do Grok 4.7 and Qwen3-30B-A3B share?
14 benchmarks have published results for both models. Grok 4.7 has 21 scored results on Noometry and Qwen3-30B-A3B has 32.