Qwen3.8 27B vs GPT-5.1 Codex mini vs Inkling Small
Inkling Small comes out ahead, 59 to 54 and 53 on our weighted score, though GPT-5.1 Codex mini is 14% cheaper per token.
Alibaba (Qwen)Qwen3.8 27B
53/100- ECI151.8
- Price$0.40 / $2.55
- Context262K
OpenAIGPT-5.1 Codex mini
54/100- ECI—
- Price$0.25 / $2.00
- Context400K
- Our pick
Thinking MachinesInkling Small
59/100- ECI150.5
- Price$0.58 / $1.44
- Context1.05M
Inkling Small is our pick
Inkling Small is the better all-round choice, scoring 59/100 against GPT-5.1 Codex mini (54) and Qwen3.8 27B (53). It leads on context window. GPT-5.1 Codex mini wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGPT-5.1 Codex miniGPT-5.1 Codex mini $0.688 · Inkling Small $0.795 · Qwen3.8 27B $0.938 per 1M tokens (3:1 blend)
- Longest contextInkling SmallInkling Small 1,048,576 · GPT-5.1 Codex mini 400,000 · Qwen3.8 27B 262,144 tokens
- Widest inputsQwen3.8 27B and Inkling SmallQwen3.8 27B: Text, Images, Video · GPT-5.1 Codex mini: Text, Images · Inkling Small: Text, Images, Audio
- Self-hostingQwen3.8 27B and Inkling SmallPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Qwen3.8 27B | GPT-5.1 Codex mini | Inkling Small |
|---|---|---|---|---|
| Price | 50% | 49 | 55 | 52 |
| Inputs & features | 30% | 70 | 60 | 70 |
| Context window | 20% | 37 | 44 | 61 |
| Overall | 100% | 53/100 | 54/100 | 59/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.8 27BAlibaba (Qwen) | GPT-5.1 Codex miniOpenAI | Inkling SmallThinking Machines |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 151.8 (best) | — | 150.5 |
| ECI rank | #54 of 165 (best) | — | #58 of 165 |
| GPQA DiamondGraduate-level science questions | — | — | 88.5% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 46.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 90.0% |
| SimpleQA VerifiedShort factual questions | — | — | 19.1% |
| Price per million tokens | |||
| Input | $0.40 | $0.25 (best) | $0.58 |
| Output | $2.55 | $2.00 | $1.44 (best) |
| Cached input | — | — | $0.116 |
| Blended (3:1) | $0.938 | $0.688 (best) | $0.795 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 49 providers | Median of 16 providers | Official Thinking Machines API |
| Limits | |||
| Context window | 262,144 tokens | 400,000 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 128,000 tokens | 1,048,576 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache-2.0 |
| API model ID | — | — | thinkingmachines/Inkling-Small |
| API providers | 53 (best) | 16 | 12 |
| Released | Aug 14, 2026 | Nov 13, 2025 | Jul 30, 2026 |
| Knowledge cutoff | — | Sep 30, 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.8 27B$9.10
- GPT-5.1 Codex mini$6.50
- Inkling Small$8.68
Which should you choose?
Which is better: Qwen3.8 27B, GPT-5.1 Codex mini or Inkling Small?
Inkling Small is the better all-round choice, scoring 59/100 against GPT-5.1 Codex mini (54) and Qwen3.8 27B (53). It leads on context window. GPT-5.1 Codex mini wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen3.8 27B, GPT-5.1 Codex mini or Inkling Small?
GPT-5.1 Codex mini is cheaper at $0.25 input / $2.00 output per million tokens (median across 16 API providers). Inkling Small costs $0.58 input / $1.44 output per million tokens (official Thinking Machines API price); Qwen3.8 27B costs $0.40 input / $2.55 output per million tokens (median across 49 API providers). At a typical mix of three input tokens to one output token, that is $0.688 per million tokens for GPT-5.1 Codex mini versus $0.795 for Inkling Small (1.2× as much) and $0.938 for Qwen3.8 27B (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.8 27B has an ECI of 151.8, GPT-5.1 Codex mini has not been scored yet and Inkling Small has an ECI of 150.5.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.8 27B, GPT-5.1 Codex mini and Inkling Small yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Inkling Small has the largest context window at 1,048,576 tokens, against 400,000 for GPT-5.1 Codex mini and 262,144 for Qwen3.8 27B. Maximum output per response: Qwen3.8 27B up to 32,768, GPT-5.1 Codex mini up to 128,000, Inkling Small up to 1,048,576 tokens.
Which can read images, PDFs, audio or video?
Qwen3.8 27B accepts text, images and video; GPT-5.1 Codex mini accepts text and images; Inkling Small accepts text, images and audio. Qwen3.8 27B handles the widest range of inputs.
Are any of these open source?
Qwen3.8 27B and Inkling Small publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.1 Codex mini is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling Small came out Jul 30, 2026; GPT-5.1 Codex mini came out Nov 13, 2025. Knowledge cutoff: GPT-5.1 Codex mini Sep 30, 2024.
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 Nov 2, 2026.
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