Kimi K2.7 Code Highspeed vs Qwen3.8 2.4T A95B vs Qwen3.8 27B
Qwen3.8 27B comes out ahead, 57 to 44 and 34 on our weighted score, and it is the cheaper option too.
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
Alibaba (Qwen)Qwen3.8 2.4T A95B
34/100- ECI—
- Price$2.00 / $6.00
- Context262K
- Our pickAlibaba (Qwen)
Qwen3.8 27B
57/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
Qwen3.8 27B is our pick
Qwen3.8 27B is the better all-round choice, scoring 57/100 against Kimi K2.7 Code Highspeed (44) and Qwen3.8 2.4T A95B (34). It leads on price. 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 priceQwen3.8 27BQwen3.8 27B $0.925 · Qwen3.8 2.4T A95B $3.00 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend)
- Longest contextAbout the sameKimi K2.7 Code Highspeed 262,144 · Qwen3.8 2.4T A95B 262,144 · Qwen3.8 27B 262,144 tokens
- Widest inputsKimi K2.7 Code Highspeed and Qwen3.8 27BKimi K2.7 Code Highspeed: Text, Images, Video · 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 | Kimi K2.7 Code Highspeed | Qwen3.8 2.4T A95B | Qwen3.8 27B |
|---|---|---|---|---|
| Price | 50% | 25 | 27 | 51 |
| Inputs & features | 30% | 80 | 45 | 80 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 44/100 | 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 | Kimi K2.7 Code HighspeedMoonshot AI | Qwen3.8 2.4T A95BAlibaba (Qwen) | Qwen3.8 27BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 149.4 |
| ECI rank | — | — | #53 of 148 |
| Price per million tokens | |||
| Input | $1.90 | $2.00 | $0.40 (best) |
| Output | $8.00 | $6.00 | $2.50 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $3.42 | $3.00 | $0.925 (best) |
| 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 | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 262,144 tokens (best) | 131,072 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Openqwen3.8-max | Open |
| API model ID | — | — | — |
| API providers | 11 | 21 | 41 (best) |
| Released | Jun 12, 2026 | Aug 12, 2026 | Aug 14, 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.
- Kimi K2.7 Code Highspeed$35.00
- Qwen3.8 2.4T A95B$32.00
- Qwen3.8 27B$9.00
Which should you choose?
Which is better: Kimi K2.7 Code Highspeed, Qwen3.8 2.4T A95B or Qwen3.8 27B?
Qwen3.8 27B is the better all-round choice, scoring 57/100 against Kimi K2.7 Code Highspeed (44) and Qwen3.8 2.4T A95B (34). It leads on price. 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, Kimi K2.7 Code Highspeed, Qwen3.8 2.4T A95B or Qwen3.8 27B?
Qwen3.8 27B is cheaper at $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); 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 $0.925 per million tokens for Qwen3.8 27B versus $3.00 for Qwen3.8 2.4T A95B (3.2× as much) and $3.42 for Kimi K2.7 Code Highspeed (3.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Kimi K2.7 Code Highspeed has not been scored yet, 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 Kimi K2.7 Code Highspeed, 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?
Kimi K2.7 Code Highspeed, Qwen3.8 2.4T A95B and Qwen3.8 27B share the same 262,144-token context window. Maximum output per response: Kimi K2.7 Code Highspeed up to 262,144, 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?
Kimi K2.7 Code Highspeed accepts text, images and video; Qwen3.8 2.4T A95B accepts text; Qwen3.8 27B accepts text, images and video. Kimi K2.7 Code Highspeed handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (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; 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.
