Inkling Small vs GPT-6.1 Sol vs Qwen3.8 27B
GPT-6.1 Sol comes out ahead, 72 to 68 and 66 on our weighted score, though Inkling Small is 5× cheaper per token.
Thinking MachinesInkling Small
68/100- ECI150.5
- Price$0.58 / $1.44
- Context1.05M
- Our pick
OpenAIGPT-6.1 Sol
72/100- ECI167.8
- Price$2.00 / $10.00
- Context1.05M
Alibaba (Qwen)Qwen3.8 27B
66/100- ECI151.8
- Price$0.40 / $2.55
- Context262K
GPT-6.1 Sol is our pick
GPT-6.1 Sol is the better all-round choice, scoring 72/100 against Inkling Small (68) and Qwen3.8 27B (66). It leads on capability and inputs & features. Inkling Small wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-6.1 SolCapabilities Index (ECI): GPT-6.1 Sol 167.8 · Qwen3.8 27B 151.8 · Inkling Small 150.5
- Lowest priceInkling SmallInkling Small $0.795 · Qwen3.8 27B $0.938 · GPT-6.1 Sol $4.00 per 1M tokens (3:1 blend)
- Longest contextGPT-6.1 Sol and Inkling SmallGPT-6.1 Sol 1,050,000 · Inkling Small 1,048,576 · Qwen3.8 27B 262,144 tokens
- Widest inputsSame inputsInkling Small: Text, Images, Audio · GPT-6.1 Sol: Text, Images, PDFs · Qwen3.8 27B: Text, Images, Video
- Self-hostingInkling Small and Qwen3.8 27BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Inkling Small | GPT-6.1 Sol | Qwen3.8 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 77 | 99 | 79 |
| Price | 25% | 52 | 20 | 49 |
| Inputs & features | 15% | 70 | 80 | 70 |
| Context window | 10% | 61 | 61 | 37 |
| Overall | 100% | 68/100 | 72/100 | 66/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Inkling SmallThinking Machines | GPT-6.1 SolOpenAI | Qwen3.8 27BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 150.5 | 167.8 (best) | 151.8 |
| ECI rank | #58 of 165 | #4 of 165 (best) | #54 of 165 |
| GPQA DiamondGraduate-level science questions | 88.5% | 95.4% (best) | — |
| FrontierMath Tiers 1–3Research-level mathematics | 46.3% | 93.7% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 90.0% | 100% (best) | — |
| SimpleQA VerifiedShort factual questions | 19.1% | 73.9% (best) | — |
| Price per million tokens | |||
| Input | $0.58 | $2.00 | $0.40 (best) |
| Output | $1.44 (best) | $10.00 | $2.55 |
| Cached input | $0.116 | $0.10 (best) | — |
| Blended (3:1) | $0.795 (best) | $4.00 | $0.938 |
| Long-context rate | Same rate | Over 272K: $4.00 / $15.00 | Same rate |
| Price source | Official Thinking Machines API | Official OpenAI API | Median of 49 providers |
| Limits | |||
| Context window | 1,048,576 tokens | 1,050,000 tokens (best) | 262,144 tokens |
| Max output | 1,048,576 tokens (best) | 128,000 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | Yes | No | No |
| Video | No | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Open |
| API model ID | thinkingmachines/Inkling-Small | gpt-6.1-sol | — |
| API providers | 12 | 33 | 53 (best) |
| Released | Jul 30, 2026 | Sep 29, 2026 | Aug 14, 2026 |
| Knowledge cutoff | — | Apr 30, 2026 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Inkling Small$8.68
- GPT-6.1 Sol$40.00
- Qwen3.8 27B$9.10
Which should you choose?
Which is better: Inkling Small, GPT-6.1 Sol or Qwen3.8 27B?
GPT-6.1 Sol is the better all-round choice, scoring 72/100 against Inkling Small (68) and Qwen3.8 27B (66). It leads on capability and inputs & features. Inkling Small wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Inkling Small, GPT-6.1 Sol or Qwen3.8 27B?
Inkling Small is cheaper at $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); GPT-6.1 Sol costs $2.00 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.795 per million tokens for Inkling Small versus $0.938 for Qwen3.8 27B (1.2× as much) and $4.00 for GPT-6.1 Sol (5× as much).
Which scores higher on benchmarks?
GPT-6.1 Sol scores higher on the Capabilities Index (ECI): GPT-6.1 Sol 167.8 (#4 of 165), Qwen3.8 27B 151.8 (#54 of 165) and Inkling Small 150.5 (#58 of 165). Their confidence ranges do not overlap (164.3–172.5 vs 149.9–153.6), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling Small, GPT-6.1 Sol and Qwen3.8 27B yet, so there is no like-for-like coding score. On overall capability, GPT-6.1 Sol 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-6.1 Sol and Inkling Small have the largest context windows (1,050,000 and 1,048,576 tokens), against 262,144 for Qwen3.8 27B. Maximum output per response: Inkling Small up to 1,048,576, GPT-6.1 Sol up to 128,000, Qwen3.8 27B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Inkling Small accepts text, images and audio; GPT-6.1 Sol accepts text, images and PDFs; Qwen3.8 27B accepts text, images and video. They handle the same number of input types.
Are any of these open source?
Inkling Small and Qwen3.8 27B publishes its weights (Apache-2.0) and can be self-hosted; GPT-6.1 Sol is proprietary.
Which is newer?
GPT-6.1 Sol is the newest, released Sep 29, 2026. Qwen3.8 27B came out Aug 14, 2026; Inkling Small came out Jul 30, 2026. Knowledge cutoff: GPT-6.1 Sol Apr 30, 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 Nov 2, 2026.
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