Inkling Small vs Qwen3.8 2.4T A95B vs Qwen3.8 27B
Inkling Small comes out ahead, 62 to 57 and 34 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 2.4T A95B
34/100- ECI—
- Price$2.00 / $6.00
- Context262K
- Alibaba (Qwen)
Qwen3.8 27B
57/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
Inkling Small is our pick
Inkling Small is the better all-round choice, scoring 62/100 against Qwen3.8 27B (57) and Qwen3.8 2.4T A95B (34). It leads on price and context window. 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 2.4T A95B $3.00 per 1M tokens (3:1 blend)
- Longest contextInkling SmallInkling Small 1,048,576 · Qwen3.8 2.4T A95B 262,144 · Qwen3.8 27B 262,144 tokens
- Widest inputsInkling Small and Qwen3.8 27BInkling Small: Text, Images, Audio · Qwen3.8 2.4T A95B: Text · Qwen3.8 27B: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Inkling Small | Qwen3.8 2.4T A95B | Qwen3.8 27B |
|---|---|---|---|---|
| Price | 50% | 58 | 27 | 51 |
| Inputs & features | 30% | 70 | 45 | 80 |
| Context window | 20% | 61 | 37 | 37 |
| Overall | 100% | 62/100 | 34/100 | 57/100 |
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 2.4T A95BAlibaba (Qwen) | Qwen3.8 27BAlibaba (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 | $2.00 | $0.40 (best) |
| Output | $1.20 (best) | $6.00 | $2.50 |
| Cached input | — | — | — |
| Blended (3:1) | $0.675 (best) | $3.00 | $0.925 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 21 providers | Median of 39 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 262,144 tokens |
| Max output | 1,048,576 tokens (best) | 131,072 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Openqwen3.8-max | Open |
| API model ID | — | — | — |
| API providers | 11 | 21 | 41 (best) |
| Released | Jul 30, 2026 | Aug 12, 2026 | Aug 14, 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 2.4T A95B$32.00
- Qwen3.8 27B$9.00
Which should you choose?
Which is better: Inkling Small, Qwen3.8 2.4T A95B or Qwen3.8 27B?
Inkling Small is the better all-round choice, scoring 62/100 against Qwen3.8 27B (57) and Qwen3.8 2.4T A95B (34). It leads on price and context window. 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 2.4T A95B or Qwen3.8 27B?
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 2.4T A95B costs $2.00 input / $6.00 output per million tokens (median across 21 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 2.4T A95B (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 2.4T A95B has not been scored yet and Qwen3.8 27B has an ECI of 149.4.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling Small, Qwen3.8 2.4T A95B and Qwen3.8 27B 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 262,144 for Qwen3.8 2.4T A95B and 262,144 for Qwen3.8 27B. Maximum output per response: Inkling Small up to 1,048,576, Qwen3.8 2.4T A95B up to 131,072, Qwen3.8 27B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Inkling Small accepts text, images and audio; Qwen3.8 2.4T A95B accepts text; Qwen3.8 27B accepts text, images and video. Inkling Small handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0 and qwen3.8-max), so you can self-host them.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Qwen3.8 2.4T A95B came out Aug 12, 2026; Inkling Small came out Jul 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 Oct 4, 2026.
