Compare / head-to-head
GPT-6 Lunavs
MiniMax M1
GPT-6 Luna leads 2 of 2 shared benchmarks. GPT-6 Luna has the larger context window (1.1M tokens).
Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.
Shared benchmarks
2 – 0
GPT-6 Luna leads
Cheaper per token
—
list price, input + output
Larger context
GPT-6 Luna
1.1M tokens
Providers
2 providers
OpenAI · MiniMax
GPT-6 Luna
OpenAI · released 2026-09-22
textvision
MiniMax M1
MiniMax · released 2025-06-16
text
- Context
- 1M
- Max out
- —
- Input /1M
- —
- Output /1M
- —
- Cached /1M
- —
- Scores
- 16 · 7 core
Quality
Benchmark matrix
2 shared · 20 only GPT-6 Luna · 14 only MiniMax M1| Benchmark | GPT-6 Luna | MiniMax M1 | Δ | Edge |
|---|---|---|---|---|
| Reported by both · 2 | ||||
| GPQA Diamond | 90.5% ↗epoch run | 70% ↗ | +20.5 pt | GPT-6 Luna |
| LMArena Elo | 1442.9 ↗ | 1363.9 ↗ | +79 | GPT-6 Luna |
| Only GPT-6 Luna reports · 20 | ||||
| APEX-Agents (Mercor) | 44.3% ↗ | not reported | — | — |
| Chess Puzzles (Epoch AI run) | 31% ↗epoch run | not reported | — | — |
| DeepSWE v1.1 | 66.6% ↗ | not reported | — | — |
| FrontierMath Tier 4 v2 (Epoch AI run) | 56.1% ↗epoch run | not reported | — | — |
| FrontierMath Tiers 1-3 v2 (Epoch AI run) | 78.9% ↗epoch run | not reported | — | — |
| Furniture Assembly (Epoch AI run) | 44.2% ↗epoch run | not reported | — | — |
| LiveBench Agentic Coding (LiveBench) | 51.2% ↗ | not reported | — | — |
| LiveBench Coding (LiveBench) | 79% ↗ | not reported | — | — |
| LiveBench Data Analysis (LiveBench) | 73.4% ↗ | not reported | — | — |
| LiveBench Instruction Following (LiveBench) | 55.9% ↗ | not reported | — | — |
| LiveBench Language (LiveBench) | 73.8% ↗ | not reported | — | — |
| LiveBench Mathematics (LiveBench) | 89.1% ↗ | not reported | — | — |
| LiveBench Reasoning (LiveBench) | 81.8% ↗ | not reported | — | — |
| LMArena Agent (LMArena) | 0.0135 ↗ | not reported | — | — |
| LMArena WebDev (LMArena) | 1578.7 ↗ | not reported | — | — |
| Mystery Game Puzzles (Epoch AI run) | 7% ↗epoch run | not reported | — | — |
| OTIS Mock AIME 2024-2025 (Epoch AI run) | 98.9% ↗epoch run | not reported | — | — |
| SAGE (Vals AI) | 48.1% ↗ | not reported | — | — |
| SimpleQA Verified | 41.4% ↗epoch run | not reported | — | — |
| Terminal-Bench 4.0 (Vals AI) | 13.6% ↗ | not reported | — | — |
| Only MiniMax M1 reports · 14 | ||||
| SWE-bench Verified | not reported | 56% ↗ | — | — |
| MMLU-Pro | not reported | 81.1% ↗ | — | — |
| AIME 2025 | not reported | 76.9% ↗ | — | — |
| AIME 2024 | not reported | 86% ↗ | — | — |
| FullStackBench | not reported | 68.3% ↗ | — | — |
| HLE (no tools) | not reported | 8.4% ↗ | — | — |
| LiveCodeBench (24/8~25/5) | not reported | 65% ↗ | — | — |
| LongBench-v2 | not reported | 61.5% ↗ | — | — |
| MATH-500 | not reported | 96.8% ↗ | — | — |
| OpenAI-MRCR (128k) | not reported | 73.4% ↗ | — | — |
| SimpleQA | not reported | 18.5% ↗ | — | — |
| TAU-bench (airline) | not reported | 62% ↗ | — | — |
| TAU-bench (retail) | not reported | 63.5% ↗ | — | — |
| ZebraLogic | not reported | 86.8% ↗ | — | — |
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-6 Luna minus MiniMax M1 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-6 Luna | MiniMax M1 | Edge |
|---|---|---|---|
| Context window | 1.1M tokens | 1M tokens | GPT-6 Luna |
| Max output | 128K tokens | — | — |
| Input price / 1M | $0.1 ↗ | — | — |
| Output price / 1M | $0.5 ↗ | — | — |
| Cached input / 1M | $0.01 ↗ | — | — |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $0.6 | — | — |
| Modalities | text · vision | text | GPT-6 Luna |
| Released | 2026-09-22 | 2025-06-16 | — |
| Cited benchmark scores | 22 | 16 | — |
Reliability
Provider status
Live from /statusMore matchups
GPT-6 Luna vs …
Models sharing the most benchmarksMore matchups
MiniMax M1 vs …
Models sharing the most benchmarksBuilt by Respan
Which one wins on your data?
Public benchmarks are a starting point. Run GPT-6 Luna and MiniMax M1 on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.