Model comparison
GPT-4o mini vs GPT-6.1 Sol
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 25.5 on the Noometry Index. GPT-4o mini costs 15× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and GPT-6.1 Sol in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6.1 Sol leads 93.7 to 10.4.
- The biggest single-benchmark swing is ARC-AGI-2: 0% for GPT-4o mini and 94.2% for GPT-6.1 Sol.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $2 / $10 for GPT-6.1 Sol.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-4o mini | GPT-6.1 Sol | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 25.5 | 65.6 |
| Released | 2024-07-18 | 2026-09-29 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 16K | 128K |
| Input $ / M tokens | $0.15 | $2 |
| Output $ / M tokens | $0.60 | $10 |
| Results tracked | 60 | 34 |
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Category by category
Coding GPT-6.1 Sol leads
GPT-4o mini: 22.0 (#335), GPT-6.1 Sol: 63.2 (#8)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| LMArena Coding | 1290 | 1487 |
| DeepSWE | — | 75.2% |
| FrontierCode | — | 50.2% |
| Aider Polyglot | 3.6% | — |
| LMArena WebDev | — | 1755 |
| SciCode | — | 55.8% |
| WeirdML | 11.8% | — |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use GPT-6.1 Sol leads
GPT-4o mini: 27.5 (#101), GPT-6.1 Sol: 39.6 (#26)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | — | 60% |
| BALROG | 17.4% | — |
| GDP.pdf | — | 32% |
Reasoning GPT-6.1 Sol leads
GPT-4o mini: 8.7 (#347), GPT-6.1 Sol: 81.9 (#2)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| ARC-AGI-2 | 0% | 94.2% |
| Chess Puzzles | 0% | 61% |
| LMArena Hard Prompts | 1267 | 1466 |
| Mystery Game Puzzles | 12% | 80% |
| Epoch Capabilities Index | 126.56 | 166.09 |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| NYT Connections (extended) | — | 95.5% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 31.7% |
| EBR-Bench | — | 54.3% |
| LiveBench Reasoning | 32.8% | — |
| DTBench | 54.4% | — |
| LiveBench Data Analysis | 50% | — |
| LMCA | 10.4% | — |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math GPT-6.1 Sol leads
GPT-4o mini: 10.4 (#314), GPT-6.1 Sol: 93.7 (#1)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0.7% | 93.7% |
| OTIS Mock AIME 2024-2025 | 6.9% | 100% |
| LMArena Math | 1267 | 1464 |
| FrontierMath Tier 4 | — | 100% |
| ProofBench | — | 99% |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge GPT-6.1 Sol leads
GPT-4o mini: 17.7 (#284), GPT-6.1 Sol: 71.8 (#4)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 37.7% | 95.4% |
| SimpleQA Verified | 8.3% | 73.9% |
| LMArena Expert | 1235 | 1502 |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal GPT-6.1 Sol leads
GPT-4o mini: 25.9 (#122), GPT-6.1 Sol: 52.7 (#5)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | 1066 | 1288 |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
| Furniture Assembly | — | 80% |
Multilingual GPT-6.1 Sol leads
GPT-4o mini: 42.0 (#199), GPT-6.1 Sol: 54.3 (#46)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1266 | 1438 |
| LMArena Chinese | 1265 | 1477 |
| LMArena Russian | 1275 | 1455 |
| LMArena French | 1297 | — |
| LMArena German | 1272 | — |
| LMArena Japanese | 1216 | — |
| LMArena Korean | 1195 | — |
| LMArena Spanish | 1276 | — |
Instruction Following GPT-6.1 Sol leads
GPT-4o mini: 61.9 (#239), GPT-6.1 Sol: 77.0 (#29)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1258 | 1468 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context GPT-6.1 Sol leads
GPT-4o mini: 39.1 (#186), GPT-6.1 Sol: 44.9 (#54)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1289 | 1465 |
Writing & Preference GPT-6.1 Sol leads
GPT-4o mini: 39.5 (#248), GPT-6.1 Sol: 63.6 (#63)
| Benchmark | GPT-4o mini | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1286 | 1447 |
| LMArena Creative Writing | 1268 | 1432 |
| LMArena Multi-Turn | 1285 | 1449 |
| Short-Story Creative Writing | 67.2% | — |
| EQ-Bench Creative Writing | 873 | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than GPT-6.1 Sol?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 25.5 on the Noometry Index. GPT-4o mini costs 15× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-4o mini or GPT-6.1 Sol?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-6.1 Sol lists at $2 and $10.
Is GPT-4o mini or GPT-6.1 Sol better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
GPT-6.1 Sol does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4o mini and GPT-6.1 Sol share?
21 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and GPT-6.1 Sol has 34.