GLM-5.3-Flash vs GPT-6 Luna vs Qwen3.7 Plus

GPT-6 Luna is the better all-round choice, scoring 84/100 against GLM-5.3-Flash (79) and Qwen3.7 Plus (68). It leads on capability and price. GLM-5.3-Flash wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3 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). GLM-5.3-Flash costs $0.15 input / $0.50 output per million tokens (official Z.AI 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 $0.237 for GLM-5.3-Flash (1.2× 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, FrontierMath Tiers 1–3 and OTIS Mock AIME 2024–2025): GPT-6 Luna 89.4%, GLM-5.3-Flash 79.9% and Qwen3.7 Plus 71.9%. On individual benchmarks: GPQA Diamond — GPT-6 Luna 90.5%, GLM-5.3-Flash 90.2%, Qwen3.7 Plus 87.9%; FrontierMath Tiers 1–3 — GPT-6 Luna 79.0%, GLM-5.3-Flash 55.8%, Qwen3.7 Plus 34.4%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, GLM-5.3-Flash 93.9%, Qwen3.7 Plus 93.3%.

There are no published SWE-bench Verified results for GLM-5.3-Flash, GPT-6 Luna 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 has the largest context window at 1,050,000 tokens, against 1,000,000 for GLM-5.3-Flash and 1,000,000 for Qwen3.7 Plus. Maximum output per response: GLM-5.3-Flash up to 131,072, GPT-6 Luna up to 128,000, Qwen3.7 Plus up to 64,000 tokens.

GLM-5.3-Flash accepts text, images, PDFs and video; GPT-6 Luna accepts text, images and PDFs; Qwen3.7 Plus accepts text, images and video. GLM-5.3-Flash handles the widest range of inputs.

GLM-5.3-Flash 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. GLM-5.3-Flash came out Aug 26, 2026; Qwen3.7 Plus came out Jun 2, 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.