Compare / head-to-head
GPT-5.5vs
MiniMax M2.1
GPT-5.5 leads 3 of 3 shared benchmarks. MiniMax M2.1 is 23.3x cheaper per token. GPT-5.5 has the larger context window (1M tokens).
Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.
Shared benchmarks
3 – 0
GPT-5.5 leads
Cheaper per token
MiniMax M2.1
23.3x cheaper, input + output
Larger context
GPT-5.5
1M tokens
Providers
2 providers
OpenAI · MiniMax
GPT-5.5
OpenAI · released 2026-04-23
textvision
MiniMax M2.1
MiniMax · released 2025-12-22
text
Quality
Benchmark matrix
3 shared · 41 only GPT-5.5 · 10 only MiniMax M2.1| Benchmark | GPT-5.5 | MiniMax M2.1 | Δ | Edge |
|---|---|---|---|---|
| Reported by both · 3 | ||||
| BrowseComp | 84.4% ↗ | 47.4% ↗ | +37 pt | GPT-5.5 |
| SimpleBench (SimpleBench) | 69% ↗ | 34.7% ↗ | +34.3 pt | GPT-5.5 |
| Toolathlon | 55.6% ↗ | 43.5% ↗ | +12.1 pt | GPT-5.5 |
| Only GPT-5.5 reports · 41 | ||||
| GPQA Diamond | 90.7% ↗epoch run | not reported | — | — |
| AIME 2026 | 100% ↗matharena ⚠ | not reported | — | — |
| LMArena Elo | 1465.6 ↗ | not reported | — | — |
| APEX-Agents (Mercor) | 55.1% ↗ | not reported | — | — |
| ARC-AGI-1 (Verified) | 95% ↗ | not reported | — | — |
| ARC-AGI-2 (Verified) | 85% ↗ | not reported | — | — |
| Chess Puzzles (Epoch AI run) | 26% ↗epoch run | not reported | — | — |
| DeepSWE v1.1 (Datacurve) | 67% ↗ | not reported | — | — |
| EBR-bench (Epoch AI run) | 34.3% ↗epoch run | not reported | — | — |
| FrontierMath Tier 1-3 | 51.7% ↗ | not reported | — | — |
| FrontierMath Tier 4 | 35.4% ↗ | not reported | — | — |
| FrontierMath Tier 4 v2 (Epoch AI run) | 72.5% ↗epoch run | not reported | — | — |
| FrontierMath Tiers 1-3 v2 (Epoch AI run) | 85.3% ↗epoch run | not reported | — | — |
| Furniture Assembly (Epoch AI run) | 44.2% ↗epoch run | not reported | — | — |
| GDPval (wins or ties) | 84.9% ↗ | not reported | — | — |
| GSO Opt@1 (GSO) | 37.3% ↗ | not reported | — | — |
| LiveBench Agentic Coding (LiveBench) | 54% ↗ | not reported | — | — |
| LiveBench Coding (LiveBench) | 82.1% ↗ | not reported | — | — |
| LiveBench Data Analysis (LiveBench) | 81.6% ↗ | not reported | — | — |
| LiveBench Instruction Following (LiveBench) | 70.7% ↗ | not reported | — | — |
| LiveBench Language (LiveBench) | 87.4% ↗ | not reported | — | — |
| LiveBench Mathematics (LiveBench) | 95.9% ↗ | not reported | — | — |
| LiveBench Reasoning (LiveBench) | 89.7% ↗ | not reported | — | — |
| LMArena Agent (LMArena) | 0.0415 ↗ | not reported | — | — |
| LMArena Vision (LMArena) | 1286.5 ↗ | not reported | — | — |
| MCP Atlas | 75.3% ↗ | not reported | — | — |
| MirrorCode (Epoch AI run) | 10% ↗epoch run | not reported | — | — |
| MMMU-Pro (no tools) | 81.2% ↗ | not reported | — | — |
| MMMU-Pro (with tools) | 83.2% ↗ | not reported | — | — |
| Mystery Game Puzzles (Epoch AI run) | 56% ↗epoch run | not reported | — | — |
| OSWorld-Verified | 78.7% ↗ | not reported | — | — |
| OTIS Mock AIME 2024-2025 (Epoch AI run) | 84.4% ↗epoch run | not reported | — | — |
| SAGE (Vals AI) | 51.5% ↗ | not reported | — | — |
| SimpleQA Verified | 63% ↗epoch run | not reported | — | — |
| SWE-Bench Pro | 58.6% ↗ | not reported | — | — |
| tau2-bench Banking Knowledge (Sierra) | 44.6% ↗ | not reported | — | — |
| Tau2-bench Telecom | 98% ↗ | not reported | — | — |
| Terminal-Bench 2.0 | 82.7% ↗ | not reported | — | — |
| Toolathlon-Verified (HKUST) | 73.5% ↗ | not reported | — | — |
| Vending-Bench 2 (Andon Labs) | 7523.84 ↗ | not reported | — | — |
| WeirdML (Håvard Tveit Ihle) | 84.9% ↗ | not reported | — | — |
| Only MiniMax M2.1 reports · 10 | ||||
| SWE-bench Verified | not reported | 74% ↗ | — | — |
| BrowseComp (context management) | not reported | 62% ↗ | — | — |
| Multi-SWE-bench | not reported | 49.4% ↗ | — | — |
| OctoCodingbench | not reported | 26.1% ↗ | — | — |
| SWE-bench Multilingual | not reported | 72.5% ↗ | — | — |
| SWE-bench Verified (Droid) | not reported | 71.3% ↗ | — | — |
| SWE-bench Verified (mini-swe-agent) | not reported | 67% ↗ | — | — |
| SWT-bench | not reported | 69.3% ↗ | — | — |
| Terminal-bench 2.0 | not reported | 47.9% ↗ | — | — |
| VIBE (Average) | not reported | 88.6% ↗ | — | — |
Scores tagged "epoch" or "matharena" are independent runs, used only where the lab has not published its own; ⚠ marks rows MathArena flags as released after the competition. Higher is better on every row. Δ is GPT-5.5 minus MiniMax M2.1 in the benchmark's own unit. "Not reported" means the lab has not published that figure; it is not a zero. ↗ opens the source.
Specs & pricing
Side by side
Official pricing pages and model cards| Spec | GPT-5.5 | MiniMax M2.1 | Edge |
|---|---|---|---|
| Context window | 1M tokens | 205K tokens | GPT-5.5 |
| Max output | 128K tokens | — | — |
| Input price / 1M | $5 ↗ | $0.3 ↗ | MiniMax M2.1 |
| Output price / 1M | $30 ↗ | $1.2 ↗ | MiniMax M2.1 |
| Cached input / 1M | $0.5 ↗ | $0.03 ↗ | MiniMax M2.1 |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $35 | $1.5 | MiniMax M2.1 |
| Modalities | text · vision | text | GPT-5.5 |
| Released | 2026-04-23 | 2025-12-22 | — |
| Cited benchmark scores | 50 | 13 | — |
Reliability
Provider status
Live from /statusMore matchups
GPT-5.5 vs …
Models sharing the most benchmarksMore matchups
MiniMax M2.1 vs …
Models sharing the most benchmarksBuilt by Respan
Which one wins on your data?
Public benchmarks are a starting point. Run GPT-5.5 and MiniMax M2.1 on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.