Model comparison
Grok 4.6 vs Qwen3.5-Flash
Grok 4.6 is the stronger model overall, scoring 56.8 to 42.3 on the Noometry Index. Qwen3.5-Flash costs 17× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.
Last verified . 29 shared benchmarks.
Alibaba (Qwen)Summary
- They share 29 benchmarks with published results for both. Grok 4.6 scores higher in 8 categories and Qwen3.5-Flash in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Grok 4.6 leads 66.8 to 36.3.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 66% for Grok 4.6 and 18.2% for Qwen3.5-Flash.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $2 / $6 for Grok 4.6.
- Qwen3.5-Flash accepts more context: 1M tokens versus 500K.
Side by side
| Grok 4.6 | Qwen3.5-Flash | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 56.8 | 42.3 |
| Released | 2026-08-12 | 2026-02-23 |
| Weights | Proprietary | Proprietary |
| Context window | 500K | 1M |
| Max output | 500K | 66K |
| Input $ / M tokens | $2 | $0.10 |
| Output $ / M tokens | $6 | $0.40 |
| Results tracked | 49 | 32 |
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Category by category
Coding Grok 4.6 leads
Grok 4.6: 58.0 (#14), Qwen3.5-Flash: 33.9 (#234)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| LMArena WebDev | 1620 | 1243 |
| LMArena Coding | 1464 | 1412 |
| ALE-Bench | 1,508 | 221.8 |
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| CursorBench | 41.4% | — |
| FrontierSWE | 25.3% | — |
| SciCode | 56.5% | — |
| WeirdML | 67.3% | — |
Agentic & Tool Use Not comparable
Grok 4.6: 39.4 (#25), Qwen3.5-Flash: —
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| Vending-Bench 2 | 9,047 | 462.69 |
| APEX-Agents | 65.3% | — |
| GDP.pdf | 17.2% | — |
Reasoning Grok 4.6 leads
Grok 4.6: 61.3 (#18), Qwen3.5-Flash: 32.9 (#63)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| Chess Puzzles | 40% | 21% |
| LMArena Hard Prompts | 1445 | 1404 |
| Mystery Game Puzzles | 34% | 20% |
| DTBench | 97.3% | 82.9% |
| LMCA | 48.5% | 29.1% |
| Epoch Capabilities Index | 156.48 | 143.98 |
| ARC-AGI-2 | 67.1% | — |
| SimpleBench | 75.9% | — |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| CritPt | 19.7% | — |
| EBR-Bench | 30.5% | — |
Math Grok 4.6 leads
Grok 4.6: 66.8 (#19), Qwen3.5-Flash: 36.3 (#117)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 66% | 18.2% |
| OTIS Mock AIME 2024-2025 | 99.2% | 84.4% |
| LMArena Math | 1416 | 1407 |
| FrontierMath Tier 4 | 31.7% | — |
| ProofBench | 51% | — |
| FrontierMath (Feb 2025 set) | — | 6.2% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Grok 4.6 leads
Grok 4.6: 63.3 (#18), Qwen3.5-Flash: 43.2 (#84)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| GPQA Diamond | 94% | 82.3% |
| SimpleQA Verified | 49.3% | 20.3% |
| LMArena Expert | 1463 | 1408 |
| Vectara Hallucination Rate | — | 10.5% |
Multimodal Not comparable
Grok 4.6: 43.9 (#18), Qwen3.5-Flash: —
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| LMArena Vision | 1265 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |
Multilingual Grok 4.6 leads
Grok 4.6: 53.3 (#67), Qwen3.5-Flash: 50.7 (#116)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1422 | 1385 |
| LMArena Chinese | 1479 | 1446 |
| LMArena French | 1458 | 1412 |
| LMArena German | 1425 | 1389 |
| LMArena Japanese | 1383 | 1369 |
| LMArena Korean | 1395 | 1344 |
| LMArena Russian | 1427 | 1379 |
| LMArena Spanish | 1408 | 1399 |
Instruction Following Grok 4.6 leads
Grok 4.6: 75.6 (#59), Qwen3.5-Flash: 72.8 (#133)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1431 | 1374 |
Long Context Grok 4.6 leads
Grok 4.6: 44.4 (#62), Qwen3.5-Flash: 42.4 (#119)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1453 | 1392 |
Writing & Preference Grok 4.6 leads
Grok 4.6: 62.5 (#77), Qwen3.5-Flash: 58.2 (#117)
| Benchmark | Grok 4.6 | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1427 | 1397 |
| LMArena Creative Writing | 1430 | 1343 |
| LMArena Multi-Turn | 1422 | 1393 |
Frequently asked questions
Is Grok 4.6 better than Qwen3.5-Flash?
Grok 4.6 is the stronger model overall, scoring 56.8 to 42.3 on the Noometry Index. Qwen3.5-Flash costs 17× 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-Flash?
Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Grok 4.6 lists at $2 and $6.
Is Grok 4.6 or Qwen3.5-Flash better for coding?
Grok 4.6 scores higher on coding benchmarks: 58.0 versus 33.9 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 500K.
How many benchmarks do Grok 4.6 and Qwen3.5-Flash share?
29 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Qwen3.5-Flash has 32.