GPT-6 Luna vs Inkling Small
GPT-6 Luna comes out ahead, 78 to 62 on our weighted score, and it is the cheaper option too.
- Our pick
OpenAIGPT-6 Luna
78/100- ECI—
- Price$0.10 / $0.50
- Context1.05M
Thinking MachinesInkling Small
62/100- ECI150.2
- Price$0.50 / $1.20
- Context1.05M
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 Inkling Small (62). It leads on capability, price and 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, 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% · Inkling Small 61.0%
- Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · Inkling Small $0.675 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGPT-6 Luna 1,050,000 · Inkling Small 1,048,576 tokens
- Widest inputsSame inputsGPT-6 Luna: Text, Images, PDFs · Inkling Small: Text, Images, Audio
- Self-hostingInkling SmallPublishes downloadable weights (Apache-2.0)
| Measure | Weight | GPT-6 Luna | Inkling Small |
|---|---|---|---|
| CapabilityShared benchmarks | 50% | 77 | 61 |
| Price | 25% | 83 | 58 |
| Inputs & features | 15% | 80 | 70 |
| Context window | 10% | 61 | 61 |
| Overall | 100% | 78/100 | 62/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-6 LunaOpenAI | Inkling SmallThinking Machines |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 150.2 |
| ECI rank | — | #47 of 148 |
| GPQA DiamondGraduate-level science questions | 90.5% (best) | 88.5% |
| FrontierMath Tiers 1–3Research-level mathematics | 79.0% (best) | 46.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 98.9% (best) | 90.0% |
| SimpleQA VerifiedShort factual questions | 41.4% (best) | 19.1% |
| Price per million tokens | ||
| Input | $0.10 (best) | $0.50 |
| Output | $0.50 (best) | $1.20 |
| Cached input | $0.01 | — |
| Blended (3:1) | $0.20 (best) | $0.675 |
| Long-context rate | Over 272K: $0.20 / $0.75 | Same rate |
| Price source | Official OpenAI API | Median of 11 providers |
| Limits | ||
| Context window | 1,050,000 tokens (best) | 1,048,576 tokens |
| Max output | 128,000 tokens | 1,048,576 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | No |
| Audio | No | Yes |
| Video | No | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | OpenApache-2.0 |
| API model ID | gpt-6-luna | — |
| API providers | 24 (best) | 11 |
| Released | Sep 22, 2026 | Jul 30, 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
- Inkling Small$7.40
Which should you choose?
Which is better: GPT-6 Luna or Inkling Small?
GPT-6 Luna is the better all-round choice, scoring 78/100 against Inkling Small (62). It leads on capability, price and 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, 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 Inkling Small?
GPT-6 Luna is cheaper at $0.10 input / $0.50 output per million tokens (official OpenAI API price). Inkling Small costs $0.50 input / $1.20 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for GPT-6 Luna versus $0.675 for Inkling Small (3.4× 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, FrontierMath Tiers 1–3, OTIS Mock AIME 2024–2025 and SimpleQA Verified): GPT-6 Luna 77.4% and Inkling Small 61.0%. On individual benchmarks: GPQA Diamond — GPT-6 Luna 90.5%, Inkling Small 88.5%; FrontierMath Tiers 1–3 — GPT-6 Luna 79.0%, Inkling Small 46.3%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, Inkling Small 90.0%; SimpleQA Verified — GPT-6 Luna 41.4%, Inkling Small 19.1%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-6 Luna and Inkling Small 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?
Their context windows are effectively the same size: GPT-6 Luna 1,050,000 and Inkling Small 1,048,576 tokens. Maximum output per response: GPT-6 Luna up to 128,000, Inkling Small up to 1,048,576 tokens.
Which can read images, PDFs, audio or video?
GPT-6 Luna accepts text, images and PDFs; Inkling Small accepts text, images and audio. They handle the same number of input types.
Are any of these open source?
Inkling Small publishes its weights (Apache-2.0) and can be self-hosted; GPT-6 Luna is proprietary.
Which is newer?
GPT-6 Luna is the newest, released Sep 22, 2026. Inkling Small came out Jul 30, 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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