Qwen3.8 2.4T A95B vs Sakana Namazu vs Kimi K2.7 Code Highspeed
Sakana Namazu comes out ahead, 51 to 44 and 34 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3.8 2.4T A95B
34/100- ECI—
- Price$2.00 / $6.00
- Context262K
- Our pick
Sakana AI
Sakana Namazu
51/100- ECI—
- Price$0.95 / $4.00
- Context262K
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
Sakana Namazu is our pick
Sakana Namazu is the better all-round choice, scoring 51/100 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 priceSakana NamazuSakana Namazu $1.71 · Qwen3.8 2.4T A95B $3.00 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend)
- Longest contextAbout the sameQwen3.8 2.4T A95B 262,144 · Sakana Namazu 262,144 · Kimi K2.7 Code Highspeed 262,144 tokens
- Widest inputsSakana Namazu and Kimi K2.7 Code HighspeedQwen3.8 2.4T A95B: Text · Sakana Namazu: Text, Images, PDFs · Kimi K2.7 Code Highspeed: Text, Images, Video
- Self-hostingQwen3.8 2.4T A95B and Kimi K2.7 Code HighspeedPublishes downloadable weights (qwen3.8-max)
| Measure | Weight | Qwen3.8 2.4T A95B | Sakana Namazu | Kimi K2.7 Code Highspeed |
|---|---|---|---|---|
| Price | 50% | 27 | 39 | 25 |
| Inputs & features | 30% | 45 | 80 | 80 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 34/100 | 51/100 | 44/100 |
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 2.4T A95BAlibaba (Qwen) | Sakana NamazuSakana AI | Kimi K2.7 Code HighspeedMoonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 | $0.95 (best) | $1.90 |
| Output | $6.00 | $4.00 (best) | $8.00 |
| Cached input | — | $0.15 | — |
| Blended (3:1) | $3.00 | $1.71 (best) | $3.42 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 21 providers | Official Sakana AI API | Median of 11 providers |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 131,072 tokens | 65,536 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Openqwen3.8-max | Proprietary | Open |
| API model ID | — | sakana-namazu | — |
| API providers | 21 (best) | 5 | 11 |
| Released | Aug 12, 2026 | Aug 3, 2026 | Jun 12, 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 2.4T A95B$32.00
- Sakana Namazu$17.50
- Kimi K2.7 Code Highspeed$35.00
Which should you choose?
Which is better: Qwen3.8 2.4T A95B, Sakana Namazu or Kimi K2.7 Code Highspeed?
Sakana Namazu is the better all-round choice, scoring 51/100 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, Qwen3.8 2.4T A95B, Sakana Namazu or Kimi K2.7 Code Highspeed?
Sakana Namazu is cheaper at $0.95 input / $4.00 output per million tokens (official Sakana AI API price). 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 $1.71 per million tokens for Sakana Namazu versus $3.00 for Qwen3.8 2.4T A95B (1.8× as much) and $3.42 for Kimi K2.7 Code Highspeed (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.8 2.4T A95B has not been scored yet, Sakana Namazu has not been scored yet and Kimi K2.7 Code Highspeed has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.8 2.4T A95B, Sakana Namazu and Kimi K2.7 Code Highspeed 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?
Qwen3.8 2.4T A95B, Sakana Namazu and Kimi K2.7 Code Highspeed share the same 262,144-token context window. Maximum output per response: Qwen3.8 2.4T A95B up to 131,072, Sakana Namazu up to 65,536, Kimi K2.7 Code Highspeed up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Qwen3.8 2.4T A95B accepts text; Sakana Namazu accepts text, images and PDFs; Kimi K2.7 Code Highspeed accepts text, images and video. Sakana Namazu handles the widest range of inputs.
Are any of these open source?
Qwen3.8 2.4T A95B and Kimi K2.7 Code Highspeed publishes its weights (qwen3.8-max) and can be self-hosted; Sakana Namazu is proprietary.
Which is newer?
Qwen3.8 2.4T A95B is the newest, released Aug 12, 2026. Sakana Namazu came out Aug 3, 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.
