Qwen3.8 27B vs GPT-6.1 Sol vs Inkling Small
GPT-6.1 Sol comes out ahead, 72 to 68 and 66 on our weighted score, though Inkling Small is 5× cheaper per token.
Alibaba (Qwen)Qwen3.8 27B
66/100- ECI151.8
- Price$0.40 / $2.55
- Context262K
- Our pick
OpenAIGPT-6.1 Sol
72/100- ECI167.8
- Price$2.00 / $10.00
- Context1.05M
Thinking MachinesInkling Small
68/100- ECI150.5
- Price$0.58 / $1.44
- Context1.05M
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 inputsQwen3.8 27B: Text, Images, Video · GPT-6.1 Sol: Text, Images, PDFs · Inkling Small: Text, Images, Audio
- Self-hostingQwen3.8 27B and Inkling SmallPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Qwen3.8 27B | GPT-6.1 Sol | Inkling Small |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 79 | 99 | 77 |
| Price | 25% | 49 | 20 | 52 |
| Inputs & features | 15% | 70 | 80 | 70 |
| Context window | 10% | 37 | 61 | 61 |
| Overall | 100% | 66/100 | 72/100 | 68/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.8 27BAlibaba (Qwen) | GPT-6.1 SolOpenAI | Inkling SmallThinking Machines |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 151.8 | 167.8 (best) | 150.5 |
| ECI rank | #54 of 165 | #4 of 165 (best) | #58 of 165 |
| GPQA DiamondGraduate-level science questions | — | 95.4% (best) | 88.5% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 93.7% (best) | 46.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 100% (best) | 90.0% |
| SimpleQA VerifiedShort factual questions | — | 73.9% (best) | 19.1% |
| Price per million tokens | |||
| Input | $0.40 (best) | $2.00 | $0.58 |
| Output | $2.55 | $10.00 | $1.44 (best) |
| Cached input | — | $0.10 (best) | $0.116 |
| Blended (3:1) | $0.938 | $4.00 | $0.795 (best) |
| Long-context rate | Same rate | Over 272K: $4.00 / $15.00 | Same rate |
| Price source | Median of 49 providers | Official OpenAI API | Official Thinking Machines API |
| Limits | |||
| Context window | 262,144 tokens | 1,050,000 tokens (best) | 1,048,576 tokens |
| 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 | Yes | No |
| Audio | No | No | Yes |
| Video | Yes | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache-2.0 |
| API model ID | — | gpt-6.1-sol | thinkingmachines/Inkling-Small |
| API providers | 53 (best) | 33 | 12 |
| Released | Aug 14, 2026 | Sep 29, 2026 | Jul 30, 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.
- Qwen3.8 27B$9.10
- GPT-6.1 Sol$40.00
- Inkling Small$8.68
Which should you choose?
Which is better: Qwen3.8 27B, GPT-6.1 Sol or Inkling Small?
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, Qwen3.8 27B, GPT-6.1 Sol or Inkling Small?
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 Qwen3.8 27B, GPT-6.1 Sol and Inkling Small 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: Qwen3.8 27B up to 32,768, GPT-6.1 Sol 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-6.1 Sol 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?
Qwen3.8 27B and Inkling Small 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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