GPT-6 Luna vs MiniMax-M3 vs Qwen3.7 Plus

GPT-6 Luna is the better all-round choice, scoring 86/100 against Qwen3.7 Plus (78) and MiniMax-M3 (73). It leads on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GPT-6 Luna has no Capabilities Index score yet.

GPT-6 Luna is cheaper at $0.10 input / $0.50 output per million tokens (official OpenAI API price). MiniMax-M3 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price); Qwen3.7 Plus costs $0.40 input / $1.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for GPT-6 Luna versus $0.525 for MiniMax-M3 (2.6× as much) and $0.70 for Qwen3.7 Plus (3.5× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): GPT-6 Luna 94.7%, Qwen3.7 Plus 90.6% and MiniMax-M3 81.0%. On individual benchmarks: GPQA Diamond — MiniMax-M3 90.9%, GPT-6 Luna 90.5%, Qwen3.7 Plus 87.9%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, Qwen3.7 Plus 93.3%, MiniMax-M3 71.1%.

There are no published SWE-bench Verified results for GPT-6 Luna, MiniMax-M3 and Qwen3.7 Plus yet, so there is no like-for-like coding score. On overall capability, GPT-6 Luna leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

GPT-6 Luna and MiniMax-M3 have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for Qwen3.7 Plus. Maximum output per response: GPT-6 Luna up to 128,000, MiniMax-M3 up to 512,000, Qwen3.7 Plus up to 64,000 tokens.

GPT-6 Luna accepts text, images and PDFs; MiniMax-M3 accepts text, images and video; Qwen3.7 Plus accepts text, images and video. They handle the same number of input types.

MiniMax-M3 publishes its weights and can be self-hosted; GPT-6 Luna and Qwen3.7 Plus is proprietary.

GPT-6 Luna is the newest, released Sep 22, 2026. Qwen3.7 Plus came out Jun 2, 2026; MiniMax-M3 came out Jun 1, 2026. Knowledge cutoff: GPT-6 Luna May 18, 2026, Qwen3.7 Plus Apr 2025.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.