Jamba Large vs Kimi K2.7 Code Highspeed vs Qwen3.8 Max Preview
Qwen3.8 Max Preview comes out ahead, 47 to 44 and 30 on our weighted score, and it is the cheaper option too.
AI21 LabsJamba Large
30/100- ECI—
- Price$2.00 / $8.00
- Context256K
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
- Our pick
Alibaba (Qwen)Qwen3.8 Max Preview
47/100- ECI—
- Price$2.00 / $6.00
- Context1M
Qwen3.8 Max Preview is our pick
Qwen3.8 Max Preview is the better all-round choice, scoring 47/100 against Kimi K2.7 Code Highspeed (44) and Jamba Large (30). It leads on price and context window. Kimi K2.7 Code Highspeed 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 priceQwen3.8 Max PreviewQwen3.8 Max Preview $3.00 · Kimi K2.7 Code Highspeed $3.42 · Jamba Large $3.50 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 Max PreviewQwen3.8 Max Preview 1,000,000 · Kimi K2.7 Code Highspeed 262,144 · Jamba Large 256,000 tokens
- Widest inputsKimi K2.7 Code Highspeed and Qwen3.8 Max PreviewJamba Large: Text · Kimi K2.7 Code Highspeed: Text, Images, Video · Qwen3.8 Max Preview: Text, Images, Video
- Self-hostingJamba Large and Kimi K2.7 Code HighspeedPublishes downloadable weights
| Measure | Weight | Jamba Large | Kimi K2.7 Code Highspeed | Qwen3.8 Max Preview |
|---|---|---|---|---|
| Price | 50% | 24 | 25 | 27 |
| Inputs & features | 30% | 35 | 80 | 70 |
| Context window | 20% | 36 | 37 | 60 |
| Overall | 100% | 30/100 | 44/100 | 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 | Jamba LargeAI21 Labs | Kimi K2.7 Code HighspeedMoonshot AI | Qwen3.8 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 | $1.90 (best) | $2.00 |
| Output | $8.00 | $8.00 | $6.00 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $3.50 | $3.42 | $3.00 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official AI21 Labs API | Median of 11 providers | Median of 6 providers |
| Limits | |||
| Context window | 256,000 tokens | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 4,096 tokens | 262,144 tokens (best) | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | Yes |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | jamba-large | — | — |
| API providers | 1 | 11 (best) | 6 |
| Released | Jul 1, 2025 | Jun 12, 2026 | Jul 19, 2026 |
| Knowledge cutoff | Aug 22, 2024 | 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.
- Jamba Large$36.00
- Kimi K2.7 Code Highspeed$35.00
- Qwen3.8 Max Preview$32.00
Which should you choose?
Which is better: Jamba Large, Kimi K2.7 Code Highspeed or Qwen3.8 Max Preview?
Qwen3.8 Max Preview is the better all-round choice, scoring 47/100 against Kimi K2.7 Code Highspeed (44) and Jamba Large (30). It leads on price and context window. Kimi K2.7 Code Highspeed 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, Jamba Large, Kimi K2.7 Code Highspeed or Qwen3.8 Max Preview?
Qwen3.8 Max Preview is cheaper at $2.00 input / $6.00 output per million tokens (median across 6 API providers). Kimi K2.7 Code Highspeed costs $1.90 input / $8.00 output per million tokens (median across 11 API providers); Jamba Large costs $2.00 input / $8.00 output per million tokens (official AI21 Labs API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Qwen3.8 Max Preview versus $3.42 for Kimi K2.7 Code Highspeed (1.1× as much) and $3.50 for Jamba Large (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Jamba Large has not been scored yet, Kimi K2.7 Code Highspeed has not been scored yet and Qwen3.8 Max Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Jamba Large, Kimi K2.7 Code Highspeed 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?
Qwen3.8 Max Preview has the largest context window at 1,000,000 tokens, against 262,144 for Kimi K2.7 Code Highspeed and 256,000 for Jamba Large. Maximum output per response: Jamba Large up to 4,096, Kimi K2.7 Code Highspeed up to 262,144, Qwen3.8 Max Preview up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Jamba Large accepts text; Kimi K2.7 Code Highspeed accepts text, images and video; Qwen3.8 Max Preview accepts text, images and video. Kimi K2.7 Code Highspeed handles the widest range of inputs.
Are any of these open source?
Jamba Large and Kimi K2.7 Code Highspeed publishes its weights and can be self-hosted; Qwen3.8 Max Preview is proprietary.
Which is newer?
Qwen3.8 Max Preview is the newest, released Jul 19, 2026. Kimi K2.7 Code Highspeed came out Jun 12, 2026; Jamba Large came out Jul 1, 2025. Knowledge cutoff: Jamba Large Aug 22, 2024, 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.
