GPT-5.6 Sol Max
| Released | 2026-07-09 |
|---|---|
| Price per 1M | $4.00 in · $20.00 out |
| Overall score | 62.5 · rank 58 |
| Context window | 1,050,000 tokens |
| Provider | OpenAI |
| Weights | Proprietary |
| Configuration | Max |
Scores
| Dimension | Score | Rank | Benchmarks |
|---|---|---|---|
| Overall: Balanced | 62.5 | 58 | 36 |
| Overall: Coding | 61.6 | 71 | 28 |
| Overall: Reasoning | 64.5 | 47 | 16 |
| Overall: Agentic work | 62.4 | 54 | 27 |
| Overall: Frontend | 60.1 | 71 | 11 |
| Coding | 61.3 | 66 | 9 |
| Agents | 62.1 | 38 | 9 |
| Reasoning | 65.8 | 35 | 9 |
| Math | 64.4 | 23 | 4 |
| Knowledge | 61.7 | 20 | 3 |
| Frontend | 59.1 | 51 | 1 |
| Multimodal | 62.1 | 11 | 1 |
| Value vs price | +6.4 | 106 |
Buzz
| Posts on X | About 35 a day |
|---|---|
| Mood | 0% positive, 15% negative |
| Hacker News | 6 mentions this week |
| Checked | 2026-11-11 |
- $CBRS Artur Meyster highlights Cerebras’ wafer-scale engineering moat. My additional bull case is that Cerebras could help frontier labs develop their next generation of models faster, accelerating the research process that leads toward recursive self-improvement. RSI means AI …
- CAN AI BUILD BETTER AI? Of the 27 models tested on @ValsAI's AI research eval, only 7 were able to improve the trained model they were given on a fixed compute budget and none of them were open models. Claude Fable 5.2 had the highest score at 37.88, while the best open model w…
- if your AI agent can only read source code, congratulations: you are testing it on training wheels every frontier lab thought autonomous agents had solved software engineering, until Columbia, Google DeepMind, and Anthropic tested them on compiled binaries here is the reality …
Evidence
Coding 61.3 ±1.2
| Benchmark | Result | Source | Date |
|---|---|---|---|
| CursorBench | 41.7% | Epoch AI | 2026-11-11 |
| FrontierSWE | 32.2% | Epoch AI | 2026-11-11 |
| DeepSWE | 72.7% | Epoch AI | 2026-11-11 |
| FrontierCode | 47.5% | Epoch AI | 2026-11-11 |
| IOI | 91.2% | Vals AI | 2026-10-29 |
| SWE-bench Verified (Vals run) | 96.2% | Vals AI | 2026-09-01 |
| SciCode | 57.1% | Epoch AI | 2026-11-11 |
| LiveCodeBench (Vals run) | 82.6% | Vals AI | 2026-09-01 |
| ProgramBench | 1.5% | Vals AI | 2026-11-09 |
Agents 62.1 ±0.8
| Benchmark | Result | Source | Date |
|---|---|---|---|
| OSWorld 2.0 | 27.3% | Epoch AI | 2026-11-11 |
| Terminal-Bench 4 | 38.5% | Terminal-Bench | 2026-06-26 |
| SRE Bench | 31.7% | Vals AI | 2026-11-05 |
| Terminal-Bench-Science | 20.0% | Vals AI | 2026-11-09 |
| Terminal-Bench 4.0 (Vals run) | 37.9% | Vals AI | 2026-11-09 |
| Terminal-Bench 2.1 (Vals run) | 85.8% | Vals AI | 2026-10-01 |
| Tax Agent Bench | 31.1% | Vals AI | 2026-11-09 |
| SkillsBench | 54.1% | Vals AI | 2026-10-29 |
| BALROG | 60.0% | Epoch AI | 2026-11-11 |
| CyberBench v1.1 | 76.3% | Vals AI | 2026-11-05 |
Reasoning 65.8 ±1.5
| Benchmark | Result | Source | Date |
|---|---|---|---|
| ARC-AGI-2 | 92.5% | Epoch AI | 2026-11-11 |
| ARC-AGI-2 (ARC Prize verified) | 92.5% | ARC Prize | 2026-11-11 |
| MysteryMechanism | 33.3% | Vals AI | 2026-11-09 |
| CritPt | 32.3% | Epoch AI | 2026-11-11 |
| ARC-AGI-1 (ARC Prize verified) | 96.5% | ARC Prize | 2026-11-11 |
| ARC-AGI-1 | 96.5% | Epoch AI | 2026-11-11 |
| GPQA Diamond | 93.5% | Epoch AI | 2026-07-09 |
| GPQA Diamond (Vals run) | 95.2% | Vals AI | 2026-09-01 |
| BioMysteryBench | 71.1% | Vals AI | 2026-11-09 |
| ARC-AGI-3 | 7.8% | ARC Prize | 2026-11-11 |
| Chess Puzzles | 59.0% | Epoch AI | 2026-10-13 |
| Mystery Game Puzzles | 58.0% | Epoch AI | 2026-07-28 |
Math 64.4 ±1.5
| Benchmark | Result | Source | Date |
|---|---|---|---|
| FrontierMath Tiers 1-3 | 89.1% | Epoch AI | 2026-07-09 |
| FrontierMath Tier 4 | 82.9% | Epoch AI | 2026-07-09 |
| OTIS Mock AIME 2024-2025 | 100.0% | Epoch AI | 2026-07-09 |
| ProofBench v1.1 | 83.0% | Vals AI | 2026-11-09 |
| ProofBench | 83.0% | Epoch AI | 2026-11-11 |
Knowledge 61.7 ±3.6
| Benchmark | Result | Source | Date |
|---|---|---|---|
| SimpleQA Verified | 69.7% | Epoch AI | 2026-08-10 |
| MMLU-Pro (Vals run) | 89.1% | Vals AI | 2026-09-01 |
| Legal Research Bench | 48.1% | Vals AI | 2026-11-09 |
Frontend 59.1 ±0.8
| Benchmark | Result | Source | Date |
|---|---|---|---|
| Vibe Code Bench v1.1 | 80.5% | Vals AI | 2026-11-09 |
Multimodal 62.1 ±2.7
| Benchmark | Result | Source | Date |
|---|---|---|---|
| MMMU-Pro (Vals run) | 88.8% | Vals AI | 2026-09-01 |
Names matched to this model
gpt-5-6-sol-max