GLM-5.3-Flash vs Mistral Small 3.2 vs GPT-6 Luna

It is close. Our weighted score puts them within a point (GPT-6 Luna 86/100, GLM-5.3-Flash 85/100, Mistral Small 3.2 52/100), so choose by what matters most for your work: GPT-6 Luna for raw capability and Mistral Small 3.2 on 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.

Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). GPT-6 Luna costs $0.10 input / $0.50 output per million tokens (official OpenAI API price); GLM-5.3-Flash costs $0.15 input / $0.50 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Small 3.2 versus $0.20 for GPT-6 Luna (1.3× as much) and $0.237 for GLM-5.3-Flash (1.6× 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%, GLM-5.3-Flash 92.0% and Mistral Small 3.2 39.7%. On individual benchmarks: GPQA Diamond — GPT-6 Luna 90.5%, GLM-5.3-Flash 90.2%, Mistral Small 3.2 49.1%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, GLM-5.3-Flash 93.9%, Mistral Small 3.2 30.3%.

There are no published SWE-bench Verified results for GLM-5.3-Flash, Mistral Small 3.2 and GPT-6 Luna 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 has the largest context window at 1,050,000 tokens, against 1,000,000 for GLM-5.3-Flash and 128,000 for Mistral Small 3.2. Maximum output per response: GLM-5.3-Flash up to 131,072, Mistral Small 3.2 up to 16,384, GPT-6 Luna up to 128,000 tokens.

GLM-5.3-Flash accepts text, images, PDFs and video; Mistral Small 3.2 accepts text and images; GPT-6 Luna accepts text, images and PDFs. GLM-5.3-Flash handles the widest range of inputs.

GLM-5.3-Flash and Mistral Small 3.2 publishes its weights and can be self-hosted; GPT-6 Luna is proprietary.

GPT-6 Luna is the newest, released Sep 22, 2026. GLM-5.3-Flash came out Aug 26, 2026; Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025, GPT-6 Luna May 18, 2026.

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.