Inkling Small vs Qwen3.8 27B vs Qwen3.8 Max Preview
Inkling Small comes out ahead, 62 to 57 and 47 on our weighted score, and it is the cheaper option too.
- Our pick
Thinking MachinesInkling Small
62/100- ECI150.2
- Price$0.50 / $1.20
- Context1.05M
Alibaba (Qwen)Qwen3.8 27B
57/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
- Alibaba (Qwen)
Qwen3.8 Max Preview
47/100- ECI—
- Price$2.00 / $6.00
- Context1M
Inkling Small is our pick
Inkling Small is the better all-round choice, scoring 62/100 against Qwen3.8 27B (57) and Qwen3.8 Max Preview (47). It leads on price. Qwen3.8 27B wins on inputs & features. 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 priceInkling SmallInkling Small $0.675 · Qwen3.8 27B $0.925 · Qwen3.8 Max Preview $3.00 per 1M tokens (3:1 blend)
- Longest contextInkling SmallInkling Small 1,048,576 · Qwen3.8 Max Preview 1,000,000 · Qwen3.8 27B 262,144 tokens
- Widest inputsSame inputsInkling Small: Text, Images, Audio · Qwen3.8 27B: Text, Images, Video · Qwen3.8 Max Preview: Text, Images, Video
- Self-hostingInkling Small and Qwen3.8 27BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Inkling Small | Qwen3.8 27B | Qwen3.8 Max Preview |
|---|---|---|---|---|
| Price | 50% | 58 | 51 | 27 |
| Inputs & features | 30% | 70 | 80 | 70 |
| Context window | 20% | 61 | 37 | 60 |
| Overall | 100% | 62/100 | 57/100 | 47/100 |
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 | Inkling SmallThinking Machines | Qwen3.8 27BAlibaba (Qwen) | Qwen3.8 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 150.2 (best) | 149.4 | — |
| ECI rank | #47 of 148 (best) | #53 of 148 | — |
| 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 | $0.50 | $0.40 (best) | $2.00 |
| Output | $1.20 (best) | $2.50 | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | $0.675 (best) | $0.925 | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 39 providers | Median of 6 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 1,000,000 tokens |
| Max output | 1,048,576 tokens (best) | 32,768 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Proprietary |
| API model ID | — | — | — |
| API providers | 11 | 41 (best) | 6 |
| Released | Jul 30, 2026 | Aug 14, 2026 | Jul 19, 2026 |
| Knowledge cutoff | — | — | — |
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$7.40
- Qwen3.8 27B$9.00
- Qwen3.8 Max Preview$32.00
Which should you choose?
Which is better: Inkling Small, Qwen3.8 27B or Qwen3.8 Max Preview?
Inkling Small is the better all-round choice, scoring 62/100 against Qwen3.8 27B (57) and Qwen3.8 Max Preview (47). It leads on price. Qwen3.8 27B wins on inputs & features. 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, Inkling Small, Qwen3.8 27B or Qwen3.8 Max Preview?
Inkling Small is cheaper at $0.50 input / $1.20 output per million tokens (median across 11 API providers). Qwen3.8 27B costs $0.40 input / $2.50 output per million tokens (median across 39 API providers); Qwen3.8 Max Preview costs $2.00 input / $6.00 output per million tokens (median across 6 API providers). At a typical mix of three input tokens to one output token, that is $0.675 per million tokens for Inkling Small versus $0.925 for Qwen3.8 27B (1.4× as much) and $3.00 for Qwen3.8 Max Preview (4.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Inkling Small has an ECI of 150.2, Qwen3.8 27B has an ECI of 149.4 and Qwen3.8 Max Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling Small, Qwen3.8 27B and Qwen3.8 Max Preview 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 1,000,000 for Qwen3.8 Max Preview and 262,144 for Qwen3.8 27B. Maximum output per response: Inkling Small up to 1,048,576, Qwen3.8 27B up to 32,768, Qwen3.8 Max Preview up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Inkling Small accepts text, images and audio; Qwen3.8 27B accepts text, images and video; Qwen3.8 Max Preview 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; Qwen3.8 Max Preview is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling Small came out Jul 30, 2026; Qwen3.8 Max Preview came out Jul 19, 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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