GLM-4.7-Flash vs GPT-6 Luna vs Mistral Small 3.2
GPT-6 Luna comes out ahead, 86 to 52 and 48 on our weighted score, though GLM-4.7-Flash is 27% cheaper per token.
Z.ai (Zhipu)GLM-4.7-Flash
48/100- ECI—
- Price$0.06 / $0.40
- Context200K
- Our pick
OpenAIGPT-6 Luna
86/100- ECI—
- Price$0.10 / $0.50
- Context1.05M
Mistral AIMistral Small 3.2
52/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
GPT-6 Luna is our pick
GPT-6 Luna is the better all-round choice, scoring 86/100 against Mistral Small 3.2 (52) and GLM-4.7-Flash (48). It leads on capability, inputs & features and context window. 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 GLM-4.7-Flash and GPT-6 Luna has no Capabilities Index score yet.
- CapabilityGPT-6 LunaShared benchmarks: GPT-6 Luna 94.7% · Mistral Small 3.2 39.7% · GLM-4.7-Flash 35.1%
- Lowest priceGLM-4.7-FlashGLM-4.7-Flash $0.145 · Mistral Small 3.2 $0.15 · GPT-6 Luna $0.20 per 1M tokens (3:1 blend)
- Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · GLM-4.7-Flash 200,000 · Mistral Small 3.2 128,000 tokens
- Widest inputsGPT-6 LunaGLM-4.7-Flash: Text · GPT-6 Luna: Text, Images, PDFs · Mistral Small 3.2: Text, Images
- Self-hostingGLM-4.7-Flash and Mistral Small 3.2Publishes downloadable weights
| Measure | Weight | GLM-4.7-Flash | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 35 | 95 | 40 |
| Price | 25% | 90 | 83 | 89 |
| Inputs & features | 15% | 35 | 80 | 50 |
| Context window | 10% | 32 | 61 | 24 |
| Overall | 100% | 48/100 | 86/100 | 52/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-4.7-FlashZ.ai (Zhipu) | GPT-6 LunaOpenAI | Mistral Small 3.2Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 131.7 |
| ECI rank | — | — | #123 of 148 |
| GPQA DiamondGraduate-level science questions | 45.1% | 90.5% (best) | 49.1% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 79.0% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 25.0% | 98.9% (best) | 30.3% |
| SimpleQA VerifiedShort factual questions | — | 41.4% | — |
| Price per million tokens | |||
| Input | $0.06 (best) | $0.10 | $0.10 |
| Output | $0.40 | $0.50 | $0.30 (best) |
| Cached input | — | $0.01 | — |
| Blended (3:1) | $0.145 (best) | $0.20 | $0.15 |
| Long-context rate | Same rate | Over 272K: $0.20 / $0.75 | Same rate |
| Price source | Median of 13 providers | Official OpenAI API | Official Mistral API |
| Limits | |||
| Context window | 200,000 tokens | 1,050,000 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 128,000 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-4.7-flash | gpt-6-luna | mistral-small-2506 |
| API providers | 19 | 24 (best) | 6 |
| Released | Jan 19, 2026 | Sep 22, 2026 | Jun 20, 2025 |
| Knowledge cutoff | Apr 2025 | May 18, 2026 | Mar 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.7-Flash$1.41
- GPT-6 Luna$2.00
- Mistral Small 3.2$1.60
Which should you choose?
Which is better: GLM-4.7-Flash, GPT-6 Luna or Mistral Small 3.2?
GPT-6 Luna is the better all-round choice, scoring 86/100 against Mistral Small 3.2 (52) and GLM-4.7-Flash (48). It leads on capability, inputs & features and context window. 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 GLM-4.7-Flash and GPT-6 Luna has no Capabilities Index score yet.
Which is cheaper, GLM-4.7-Flash, GPT-6 Luna or Mistral Small 3.2?
GLM-4.7-Flash is cheaper at $0.06 input / $0.40 output per million tokens (median across 13 API providers; free on Z.AI). Mistral Small 3.2 costs $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). At a typical mix of three input tokens to one output token, that is $0.145 per million tokens for GLM-4.7-Flash versus $0.15 for Mistral Small 3.2 (1× as much) and $0.20 for GPT-6 Luna (1.4× as much).
Which scores higher on benchmarks?
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%, Mistral Small 3.2 39.7% and GLM-4.7-Flash 35.1%. On individual benchmarks: GPQA Diamond — GPT-6 Luna 90.5%, Mistral Small 3.2 49.1%, GLM-4.7-Flash 45.1%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, Mistral Small 3.2 30.3%, GLM-4.7-Flash 25.0%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7-Flash, GPT-6 Luna and Mistral Small 3.2 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.
Which has the bigger context window?
GPT-6 Luna has the largest context window at 1,050,000 tokens, against 200,000 for GLM-4.7-Flash and 128,000 for Mistral Small 3.2. Maximum output per response: GLM-4.7-Flash up to 131,072, GPT-6 Luna up to 128,000, Mistral Small 3.2 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-Flash accepts text; GPT-6 Luna accepts text, images and PDFs; Mistral Small 3.2 accepts text and images. GPT-6 Luna handles the widest range of inputs.
Are any of these open source?
GLM-4.7-Flash and Mistral Small 3.2 publishes its weights and can be self-hosted; GPT-6 Luna is proprietary.
Which is newer?
GPT-6 Luna is the newest, released Sep 22, 2026. GLM-4.7-Flash came out Jan 19, 2026; Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: GLM-4.7-Flash Apr 2025, GPT-6 Luna May 18, 2026, Mistral Small 3.2 Mar 2025.
How do you decide the winner?
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.
