Qwen3.8 27B vs Kimi K2.7 Code Highspeed vs Inkling Small
Inkling Small comes out ahead, 62 to 57 and 44 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3.8 27B
57/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
- Our pick
Thinking MachinesInkling Small
62/100- ECI150.2
- Price$0.50 / $1.20
- Context1.05M
Inkling Small is our pick
Inkling Small is the better all-round choice, scoring 62/100 against Qwen3.8 27B (57) and Kimi K2.7 Code Highspeed (44). It leads on price and context window. 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 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend)
- Longest contextInkling SmallInkling Small 1,048,576 · Qwen3.8 27B 262,144 · Kimi K2.7 Code Highspeed 262,144 tokens
- Widest inputsSame inputsQwen3.8 27B: Text, Images, Video · Kimi K2.7 Code Highspeed: Text, Images, Video · Inkling Small: Text, Images, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3.8 27B | Kimi K2.7 Code Highspeed | Inkling Small |
|---|---|---|---|---|
| Price | 50% | 51 | 25 | 58 |
| Inputs & features | 30% | 80 | 80 | 70 |
| Context window | 20% | 37 | 37 | 61 |
| Overall | 100% | 57/100 | 44/100 | 62/100 |
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) | Kimi K2.7 Code HighspeedMoonshot AI | Inkling SmallThinking Machines |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.4 | — | 150.2 (best) |
| ECI rank | #53 of 148 | — | #47 of 148 (best) |
| 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 (best) | $1.90 | $0.50 |
| Output | $2.50 | $8.00 | $1.20 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.925 | $3.42 | $0.675 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 39 providers | Median of 11 providers | Median of 11 providers |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 262,144 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 | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Open | OpenApache-2.0 |
| API model ID | — | — | — |
| API providers | 41 (best) | 11 | 11 |
| Released | Aug 14, 2026 | Jun 12, 2026 | Jul 30, 2026 |
| Knowledge cutoff | — | Jan 2025 | — |
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$9.00
- Kimi K2.7 Code Highspeed$35.00
- Inkling Small$7.40
Which should you choose?
Which is better: Qwen3.8 27B, Kimi K2.7 Code Highspeed or Inkling Small?
Inkling Small is the better all-round choice, scoring 62/100 against Qwen3.8 27B (57) and Kimi K2.7 Code Highspeed (44). It leads on price and context window. 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, Kimi K2.7 Code Highspeed or Inkling Small?
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); Kimi K2.7 Code Highspeed costs $1.90 input / $8.00 output per million tokens (median across 11 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 $3.42 for Kimi K2.7 Code Highspeed (5.1× 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 149.4, Kimi K2.7 Code Highspeed has not been scored yet and Inkling Small has an ECI of 150.2.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.8 27B, Kimi K2.7 Code Highspeed 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 262,144 for Qwen3.8 27B and 262,144 for Kimi K2.7 Code Highspeed. Maximum output per response: Qwen3.8 27B up to 32,768, Kimi K2.7 Code Highspeed up to 262,144, Inkling Small up to 1,048,576 tokens.
Which can read images, PDFs, audio or video?
Qwen3.8 27B accepts text, images and video; Kimi K2.7 Code Highspeed accepts text, images and video; Inkling Small accepts text, images and audio. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling Small came out Jul 30, 2026; Kimi K2.7 Code Highspeed came out Jun 12, 2026. Knowledge cutoff: Kimi K2.7 Code Highspeed Jan 2025.
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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