GPT-6 Luna vs Qwen3.5 Flash
GPT-6 Luna comes out ahead, 78 to 65 on our weighted score, though Qwen3.5 Flash is 13% cheaper per token.
- Our pick
OpenAIGPT-6 Luna
78/100- ECI—
- Price$0.10 / $0.50
- Context1.05M
Alibaba (Qwen)Qwen3.5 Flash
65/100- ECI144.0
- Price$0.10 / $0.40
- Context1M
Add a model
Make it a three-way comparison.
GPT-6 Luna is our pick
GPT-6 Luna is the better all-round choice, scoring 78/100 against Qwen3.5 Flash (65). It leads on capability. Qwen3.5 Flash wins on price. 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, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6 Luna has no Capabilities Index score yet.
- CapabilityGPT-6 LunaShared benchmarks: GPT-6 Luna 77.4% · Qwen3.5 Flash 51.3%
- Lowest priceQwen3.5 FlashQwen3.5 Flash $0.175 · GPT-6 Luna $0.20 per 1M tokens (3:1 blend)
- Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · Qwen3.5 Flash 1,000,000 tokens
- Widest inputsSame inputsGPT-6 Luna: Text, Images, PDFs · Qwen3.5 Flash: Text, Images, Video
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | GPT-6 Luna | Qwen3.5 Flash |
|---|---|---|---|
| CapabilityShared benchmarks | 50% | 77 | 51 |
| Price | 25% | 83 | 86 |
| Inputs & features | 15% | 80 | 80 |
| Context window | 10% | 61 | 60 |
| Overall | 100% | 78/100 | 65/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-6 LunaOpenAI | Qwen3.5 FlashAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 144.0 |
| ECI rank | — | #82 of 148 |
| GPQA DiamondGraduate-level science questions | 90.5% (best) | 82.3% |
| FrontierMath Tiers 1–3Research-level mathematics | 79.0% (best) | 18.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 98.9% (best) | 84.4% |
| SimpleQA VerifiedShort factual questions | 41.4% (best) | 20.3% |
| Price per million tokens | ||
| Input | $0.10 | $0.10 |
| Output | $0.50 | $0.40 (best) |
| Cached input | $0.01 | $0.01 |
| Blended (3:1) | $0.20 | $0.175 (best) |
| Long-context rate | Over 272K: $0.20 / $0.75 | Same rate |
| Price source | Official OpenAI API | Official Alibaba API |
| Limits | ||
| Context window | 1,050,000 tokens (best) | 1,000,000 tokens |
| Max output | 128,000 tokens (best) | 65,536 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | gpt-6-luna | qwen3.5-flash |
| API providers | 24 (best) | 8 |
| Released | Sep 22, 2026 | Feb 23, 2026 |
| Knowledge cutoff | May 18, 2026 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-6 Luna$2.00
- Qwen3.5 Flash$1.80
Which should you choose?
Which is better: GPT-6 Luna or Qwen3.5 Flash?
GPT-6 Luna is the better all-round choice, scoring 78/100 against Qwen3.5 Flash (65). It leads on capability. Qwen3.5 Flash wins on price. 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, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6 Luna has no Capabilities Index score yet.
Which is cheaper, GPT-6 Luna or Qwen3.5 Flash?
Qwen3.5 Flash is cheaper at $0.10 input / $0.40 output per million tokens (official Alibaba 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 $0.175 per million tokens for Qwen3.5 Flash versus $0.20 for GPT-6 Luna (1.1× 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, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified): GPT-6 Luna 77.4% and Qwen3.5 Flash 51.3%. On individual benchmarks: GPQA Diamond — GPT-6 Luna 90.5%, Qwen3.5 Flash 82.3%; FrontierMath Tiers 1–3 — GPT-6 Luna 79.0%, Qwen3.5 Flash 18.3%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, Qwen3.5 Flash 84.4%; SimpleQA Verified — GPT-6 Luna 41.4%, Qwen3.5 Flash 20.3%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-6 Luna and Qwen3.5 Flash 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. Both 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 1,000,000 for Qwen3.5 Flash. Maximum output per response: GPT-6 Luna up to 128,000, Qwen3.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-6 Luna accepts text, images and PDFs; Qwen3.5 Flash accepts text, images and video. They handle the same number of input types.
Are any of these open source?
No. GPT-6 Luna and Qwen3.5 Flash are proprietary and only available through APIs and apps.
Which is newer?
GPT-6 Luna is the newest, released Sep 22, 2026. Qwen3.5 Flash came out Feb 23, 2026. Knowledge cutoff: GPT-6 Luna May 18, 2026.
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.
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