Model comparison
Grok 4.6 vs Qwen3.5-9B
Grok 4.6 is the stronger model overall, scoring 56.8 to 33.3 on the Noometry Index. Qwen3.5-9B costs 27× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Last verified . 8 shared benchmarks.
Alibaba (Qwen)Summary
- They share 8 benchmarks with published results for both. Grok 4.6 scores higher in 5 categories and Qwen3.5-9B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.6 leads 61.3 to 22.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 99.2% for Grok 4.6 and 61.7% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $2 / $6 for Grok 4.6.
- Grok 4.6 accepts more context: 500K tokens versus 262K.
- Qwen3.5-9B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.6 | Qwen3.5-9B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 56.8 | 33.3 |
| Released | 2026-08-12 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 500K | 262K |
| Max output | 500K | 66K |
| Input $ / M tokens | $2 | $0.10 |
| Output $ / M tokens | $6 | $0.15 |
| Results tracked | 49 | 10 |
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Category by category
Coding Grok 4.6 leads
Grok 4.6: 58.0 (#14), Qwen3.5-9B: 35.3 (#213)
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| SciCode | 56.5% | 27.5% |
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| CursorBench | 41.4% | — |
| LMArena WebDev | 1620 | — |
| FrontierSWE | 25.3% | — |
| WeirdML | 67.3% | — |
| LMArena Coding | 1464 | — |
| ALE-Bench | 1,508 | — |
Agentic & Tool Use Grok 4.6 leads
Grok 4.6: 39.4 (#25), Qwen3.5-9B: 14.4 (#143)
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | — | 9.2% |
| APEX-Agents | 65.3% | — |
| GDP.pdf | 17.2% | — |
| Vending-Bench 2 | 9,047 | — |
Reasoning Grok 4.6 leads
Grok 4.6: 61.3 (#18), Qwen3.5-9B: 22.5 (#178)
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| CritPt | 19.7% | 0.3% |
| Chess Puzzles | 40% | 12% |
| DTBench | 97.3% | 71.2% |
| LMCA | 48.5% | 24.5% |
| Epoch Capabilities Index | 156.48 | 139.45 |
| ARC-AGI-2 | 67.1% | — |
| SimpleBench | 75.9% | — |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| EBR-Bench | 30.5% | — |
| LMArena Hard Prompts | 1445 | — |
| Mystery Game Puzzles | 34% | — |
Math Grok 4.6 leads
Grok 4.6: 66.8 (#19), Qwen3.5-9B: 33.5 (#174)
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 99.2% | 61.7% |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | — | 48.5% |
| ProofBench | 51% | — |
| LMArena Math | 1416 | — |
Knowledge Grok 4.6 leads
Grok 4.6: 63.3 (#18), Qwen3.5-9B: 46.0 (#77)
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | 94% | 79% |
| SimpleQA Verified | 49.3% | — |
| LMArena Expert | 1463 | — |
Multimodal Not comparable
Grok 4.6: 43.9 (#18), Qwen3.5-9B: —
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Vision | 1265 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |
Multilingual Not comparable
Grok 4.6: 53.3 (#67), Qwen3.5-9B: —
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Non-English | 1422 | — |
| LMArena Chinese | 1479 | — |
| LMArena French | 1458 | — |
| LMArena German | 1425 | — |
| LMArena Japanese | 1383 | — |
| LMArena Korean | 1395 | — |
| LMArena Russian | 1427 | — |
| LMArena Spanish | 1408 | — |
Instruction Following Not comparable
Grok 4.6: 75.6 (#59), Qwen3.5-9B: —
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Instruction Following | 1431 | — |
Long Context Not comparable
Grok 4.6: 44.4 (#62), Qwen3.5-9B: —
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Longer Query | 1453 | — |
Writing & Preference Not comparable
Grok 4.6: 62.5 (#77), Qwen3.5-9B: —
| Benchmark | Grok 4.6 | Qwen3.5-9B |
|---|---|---|
| LMArena Text | 1427 | — |
| LMArena Creative Writing | 1430 | — |
| LMArena Multi-Turn | 1422 | — |
Frequently asked questions
Is Grok 4.6 better than Qwen3.5-9B?
Grok 4.6 is the stronger model overall, scoring 56.8 to 33.3 on the Noometry Index. Qwen3.5-9B costs 27× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Which is cheaper, Grok 4.6 or Qwen3.5-9B?
Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; Grok 4.6 lists at $2 and $6.
Is Grok 4.6 or Qwen3.5-9B better for coding?
Grok 4.6 scores higher on coding benchmarks: 58.0 versus 35.3 in the Noometry coding category.
Which has the bigger context window?
Grok 4.6 does, with 500K tokens against 262K.
How many benchmarks do Grok 4.6 and Qwen3.5-9B share?
8 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Qwen3.5-9B has 10.