Model comparison
Grok 4.5 vs Qwen3 32B
Grok 4.5 is the stronger model overall, scoring 55.0 to 38.8 on the Noometry Index. Qwen3 32B costs 2.4× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. Grok 4.5 scores higher in 9 categories and Qwen3 32B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.0 to 19.6.
- The biggest single-benchmark swing is Chess Puzzles: 36% for Grok 4.5 and 5% for Qwen3 32B.
- Qwen3 32B is cheaper at $0.70 / $2.80 per million input/output tokens, against $2 / $6 for Grok 4.5.
- Grok 4.5 accepts more context: 500K tokens versus 131K.
- Qwen3 32B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.5 | Qwen3 32B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 55.0 | 38.8 |
| Released | 2026-07-08 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 500K | 131K |
| Max output | 500K | 16K |
| Input $ / M tokens | $2 | $0.70 |
| Output $ / M tokens | $6 | $2.80 |
| Results tracked | 52 | 26 |
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Category by category
Coding Grok 4.5 leads
Grok 4.5: 51.7 (#34), Qwen3 32B: 37.3 (#184)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| SciCode | 54.1% | 35.4% |
| LMArena Coding | 1473 | 1358 |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.4% | — |
| Aider Polyglot | — | 40% |
| LMArena WebDev | 1552 | — |
| WeirdML | 46.4% | — |
| ALE-Bench | 1,309 | — |
Agentic & Tool Use Grok 4.5 leads
Grok 4.5: 44.4 (#15), Qwen3 32B: 32.3 (#58)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| APEX-Agents | 56.2% | — |
| Berkeley Function Calling Leaderboard | — | 48.7% |
| τ²-bench Banking | 47.9% | — |
| PostTrainBench | 23.4% | — |
| GBAEval | 65.4% | — |
| GDP.pdf | 14% | — |
| LMArena Search | 1213 | — |
| Vending-Bench 2 | 3,887 | — |
Reasoning Grok 4.5 leads
Grok 4.5: 56.0 (#23), Qwen3 32B: 19.6 (#233)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| Kagi LLM Benchmark | 83.5% | 54.9% |
| CritPt | 15.4% | 0.3% |
| Chess Puzzles | 36% | 5% |
| LMArena Hard Prompts | 1462 | 1335 |
| DTBench | 96.5% | 67.5% |
| LMCA | 45.2% | 17.3% |
| Epoch Capabilities Index | 154.02 | 138.51 |
| ARC-AGI-2 | 52.6% | — |
| SimpleBench | 70% | — |
| NYT Connections (extended) | 79.9% | — |
| ARC-AGI-1 | 87.2% | — |
| Surface Evolver Bench | 74.4% | — |
Math Grok 4.5 leads
Grok 4.5: 60.7 (#29), Qwen3 32B: 37.9 (#89)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 97.8% | 66.9% |
| LMArena Math | 1457 | 1399 |
| FrontierMath (Tiers 1-3) | 57.2% | — |
| FrontierMath Tier 4 | 24.4% | — |
| ProofBench | 31% | — |
Knowledge Grok 4.5 leads
Grok 4.5: 62.3 (#21), Qwen3 32B: 40.0 (#112)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| GPQA Diamond | 93.4% | 65.7% |
| LMArena Expert | 1466 | 1362 |
| SimpleQA Verified | 48.3% | — |
| Vectara Hallucination Rate | — | 5.9% |
Multimodal Not comparable
Grok 4.5: 37.8 (#63), Qwen3 32B: —
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| LMArena Vision | 1287 | — |
| Blueprint-Bench 2 | 27.3% | — |
| Furniture Assembly | 22.5% | — |
| LMArena Document | 1452 | — |
Multilingual Grok 4.5 leads
Grok 4.5: 54.5 (#43), Qwen3 32B: 45.8 (#162)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1439 | 1317 |
| LMArena Chinese | 1497 | 1357 |
| LMArena German | 1448 | 1341 |
| LMArena Russian | 1447 | 1311 |
| LMArena French | 1458 | — |
| LMArena Japanese | 1425 | — |
| LMArena Korean | 1402 | — |
| LMArena Spanish | 1452 | — |
Instruction Following Grok 4.5 leads
Grok 4.5: 76.3 (#45), Qwen3 32B: 69.1 (#174)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1446 | 1305 |
Long Context Grok 4.5 leads
Grok 4.5: 44.8 (#54), Qwen3 32B: 43.7 (#83)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1463 | 1327 |
| Fiction.LiveBench | — | 74.2% |
Writing & Preference Grok 4.5 leads
Grok 4.5: 65.9 (#40), Qwen3 32B: 53.1 (#158)
| Benchmark | Grok 4.5 | Qwen3 32B |
|---|---|---|
| LMArena Text | 1448 | 1340 |
| LMArena Creative Writing | 1442 | 1297 |
| LMArena Multi-Turn | 1457 | 1331 |
| EQ-Bench Creative Writing | 1579 | — |
Frequently asked questions
Is Grok 4.5 better than Qwen3 32B?
Grok 4.5 is the stronger model overall, scoring 55.0 to 38.8 on the Noometry Index. Qwen3 32B costs 2.4× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Which is cheaper, Grok 4.5 or Qwen3 32B?
Qwen3 32B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Grok 4.5 lists at $2 and $6.
Is Grok 4.5 or Qwen3 32B better for coding?
Grok 4.5 scores higher on coding benchmarks: 51.7 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
Grok 4.5 does, with 500K tokens against 131K.
How many benchmarks do Grok 4.5 and Qwen3 32B share?
22 benchmarks have published results for both models. Grok 4.5 has 52 scored results on Noometry and Qwen3 32B has 26.