Model comparison
GPT-5.6 Sol vs Grok 4.20 Multi-Agent
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 45.5 on the Noometry Index. Grok 4.20 Multi-Agent costs 5.1× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. GPT-5.6 Sol scores higher in 9 categories and Grok 4.20 Multi-Agent in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Sol leads 85.5 to 36.6.
- Grok 4.20 Multi-Agent is cheaper at $1.25 / $2.50 per million input/output tokens, against $4 / $20 for GPT-5.6 Sol.
- GPT-5.6 Sol accepts more context: 1.05M tokens versus 1M.
Side by side
| GPT-5.6 Sol | Grok 4.20 Multi-Agent | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 64.4 | 45.5 |
| Released | 2026-07-09 | 2026-03-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1M |
| Max output | 128K | 30K |
| Input $ / M tokens | $4 | $1.25 |
| Output $ / M tokens | $20 | $2.50 |
| Results tracked | 64 | 20 |
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Category by category
Coding GPT-5.6 Sol leads
GPT-5.6 Sol: 61.1 (#7), Grok 4.20 Multi-Agent: 42.4 (#91)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Coding | 1493 | 1458 |
| DeepSWE | 72.7% | — |
| FrontierCode | 47.5% | — |
| CursorBench | 41.7% | — |
| LMArena WebDev | 1619 | — |
| FrontierSWE | 32.2% | — |
| SciCode | 57.1% | — |
| WeirdML | 89.4% | — |
| MirrorCode | 20% | — |
| ALE-Bench | 2,177 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Sol: 50.2 (#7), Grok 4.20 Multi-Agent: —
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Search | 1257 | 1204 |
| APEX-Agents | 51.4% | — |
| OSWorld 2.0 | 27.3% | — |
| τ²-bench Banking | 46.9% | — |
| PostTrainBench | 36.2% | — |
| BALROG | 60% | — |
| GBAEval | 52.6% | — |
| GDP.pdf | 30.7% | — |
| Vending-Bench 2 | 9,619 | — |
Reasoning GPT-5.6 Sol leads
GPT-5.6 Sol: 74.7 (#6), Grok 4.20 Multi-Agent: 42.4 (#44)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| NYT Connections (extended) | 93.8% | 89.6% |
| LMArena Hard Prompts | 1481 | 1448 |
| ARC-AGI-2 | 92.5% | — |
| SimpleBench | 71.7% | — |
| Kagi LLM Benchmark | 67% | — |
| ARC-AGI-1 | 97.5% | — |
| CritPt | 32.3% | — |
| Chess Puzzles | 64% | — |
| EnigmaEval | 37.1% | — |
| EBR-Bench | 44.8% | — |
| Mystery Game Puzzles | 58% | — |
| DTBench | 96% | — |
| LMCA | 59.2% | — |
| Surface Evolver Bench | 93.1% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 161.99 | — |
Math GPT-5.6 Sol leads
GPT-5.6 Sol: 85.5 (#7), Grok 4.20 Multi-Agent: 36.6 (#106)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Math | 1472 | 1441 |
| FrontierMath (Tiers 1-3) | 89.1% | — |
| FrontierMath Tier 4 | 82.9% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| FrontierMath Erdős | 0% | — |
Knowledge GPT-5.6 Sol leads
GPT-5.6 Sol: 64.3 (#16), Grok 4.20 Multi-Agent: 39.7 (#116)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Expert | 1517 | 1445 |
| GPQA Diamond | 93.5% | — |
| SimpleQA Verified | 69.7% | — |
| Vectara Hallucination Rate | 12.4% | — |
Multimodal GPT-5.6 Sol leads
GPT-5.6 Sol: 48.9 (#8), Grok 4.20 Multi-Agent: 39.8 (#44)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Vision | 1281 | 1259 |
| Blueprint-Bench 2 | 33.6% | — |
| Furniture Assembly | 56.7% | — |
| LMArena Document | 1483 | — |
Multilingual Too close to call
GPT-5.6 Sol: 55.4 (#32), Grok 4.20 Multi-Agent: 54.6 (#40)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Non-English | 1450 | 1440 |
| LMArena Chinese | 1523 | 1475 |
| LMArena French | 1475 | 1467 |
| LMArena German | 1476 | 1456 |
| LMArena Japanese | 1475 | 1405 |
| LMArena Korean | 1434 | 1416 |
| LMArena Russian | 1466 | 1457 |
| LMArena Spanish | 1449 | 1447 |
Instruction Following GPT-5.6 Sol leads
GPT-5.6 Sol: 77.8 (#16), Grok 4.20 Multi-Agent: 75.0 (#80)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Instruction Following | 1480 | 1420 |
Long Context GPT-5.6 Sol leads
GPT-5.6 Sol: 45.3 (#42), Grok 4.20 Multi-Agent: 43.7 (#84)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Longer Query | 1479 | 1430 |
Writing & Preference GPT-5.6 Sol leads
GPT-5.6 Sol: 73.5 (#12), Grok 4.20 Multi-Agent: 64.1 (#57)
| Benchmark | GPT-5.6 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text | 1456 | 1450 |
| LMArena Creative Writing | 1450 | 1435 |
| LMArena Multi-Turn | 1456 | 1451 |
| EQ-Bench Creative Writing | 1972 | — |
| EQ-Bench 4 | 1250 | — |
Frequently asked questions
Is GPT-5.6 Sol better than Grok 4.20 Multi-Agent?
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 45.5 on the Noometry Index. Grok 4.20 Multi-Agent costs 5.1× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-5.6 Sol or Grok 4.20 Multi-Agent?
Grok 4.20 Multi-Agent is cheaper. It lists at $1.25 per million input tokens and $2.50 per million output tokens; GPT-5.6 Sol lists at $4 and $20.
Is GPT-5.6 Sol or Grok 4.20 Multi-Agent better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 61.1 versus 42.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Sol does, with 1.05M tokens against 1M.
How many benchmarks do GPT-5.6 Sol and Grok 4.20 Multi-Agent share?
20 benchmarks have published results for both models. GPT-5.6 Sol has 64 scored results on Noometry and Grok 4.20 Multi-Agent has 20.