Kimi K2.7 Code Highspeed vs Nex-N2-Pro vs Qwen3.8 Max Preview
Nex-N2-Pro comes out ahead, 53 to 47 and 44 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
- Our pick
Nex AGI
Nex-N2-Pro
53/100- ECI—
- Price$0.50 / $2.50
- Context262K
Alibaba (Qwen)Qwen3.8 Max Preview
47/100- ECI—
- Price$2.00 / $6.00
- Context1M
Nex-N2-Pro is our pick
Nex-N2-Pro is the better all-round choice, scoring 53/100 against Qwen3.8 Max Preview (47) and Kimi K2.7 Code Highspeed (44). It leads on price. Kimi K2.7 Code Highspeed wins on inputs & features. Qwen3.8 Max Preview wins on 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 priceNex-N2-ProNex-N2-Pro $1.00 · Qwen3.8 Max Preview $3.00 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 Max PreviewQwen3.8 Max Preview 1,000,000 · Kimi K2.7 Code Highspeed 262,144 · Nex-N2-Pro 262,144 tokens
- Widest inputsKimi K2.7 Code Highspeed and Qwen3.8 Max PreviewKimi K2.7 Code Highspeed: Text, Images, Video · Nex-N2-Pro: Text, Images · Qwen3.8 Max Preview: Text, Images, Video
- Self-hostingKimi K2.7 Code Highspeed and Nex-N2-ProPublishes downloadable weights
| Measure | Weight | Kimi K2.7 Code Highspeed | Nex-N2-Pro | Qwen3.8 Max Preview |
|---|---|---|---|---|
| Price | 50% | 25 | 50 | 27 |
| Inputs & features | 30% | 80 | 70 | 70 |
| Context window | 20% | 37 | 37 | 60 |
| Overall | 100% | 44/100 | 53/100 | 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 | Kimi K2.7 Code HighspeedMoonshot AI | Nex-N2-ProNex AGI | Qwen3.8 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.90 | $0.50 (best) | $2.00 |
| Output | $8.00 | $2.50 (best) | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.42 | $1.00 (best) | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 1 providers | Median of 6 providers |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 262,144 tokens (best) | 262,144 tokens (best) | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | 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 | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | — | — |
| API providers | 11 (best) | 1 | 6 |
| Released | Jun 12, 2026 | Jun 2, 2026 | Jul 19, 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
- Nex-N2-Pro$10.00
- Qwen3.8 Max Preview$32.00
Which should you choose?
Which is better: Kimi K2.7 Code Highspeed, Nex-N2-Pro or Qwen3.8 Max Preview?
Nex-N2-Pro is the better all-round choice, scoring 53/100 against Qwen3.8 Max Preview (47) and Kimi K2.7 Code Highspeed (44). It leads on price. Kimi K2.7 Code Highspeed wins on inputs & features. Qwen3.8 Max Preview wins on 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, Kimi K2.7 Code Highspeed, Nex-N2-Pro or Qwen3.8 Max Preview?
Nex-N2-Pro is cheaper at $0.50 input / $2.50 output per million tokens (median across 1 API provider). Qwen3.8 Max Preview costs $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). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for Nex-N2-Pro versus $3.00 for Qwen3.8 Max Preview (3× as much) and $3.42 for Kimi K2.7 Code Highspeed (3.4× 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, Nex-N2-Pro 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 Kimi K2.7 Code Highspeed, Nex-N2-Pro 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 262,144 for Nex-N2-Pro. Maximum output per response: Kimi K2.7 Code Highspeed up to 262,144, Nex-N2-Pro up to 262,144, Qwen3.8 Max Preview up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Kimi K2.7 Code Highspeed accepts text, images and video; Nex-N2-Pro accepts text and images; 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?
Kimi K2.7 Code Highspeed and Nex-N2-Pro 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; Nex-N2-Pro came out Jun 2, 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.
