Qwen3.7 Flash vs Kimi K2.7 Code Highspeed vs DeepSeek V4 Flash
Qwen3.7 Flash comes out ahead, 86 to 68 and 44 on our weighted score, and it is the cheaper option too.
- Our pick
Alibaba (Qwen)Qwen3.7 Flash
86/100- ECI144.6
- Price$0.03 / $0.13
- Context1M
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
DeepSeekDeepSeek V4 Flash
68/100- ECI146.1
- Price$0.14 / $0.28
- Context1M
Qwen3.7 Flash is our pick
Qwen3.7 Flash is the better all-round choice, scoring 86/100 against DeepSeek V4 Flash (68) and Kimi K2.7 Code Highspeed (44). 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 priceQwen3.7 FlashQwen3.7 Flash $0.055 · DeepSeek V4 Flash $0.175 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend)
- Longest contextQwen3.7 Flash and DeepSeek V4 FlashQwen3.7 Flash 1,000,000 · DeepSeek V4 Flash 1,000,000 · Kimi K2.7 Code Highspeed 262,144 tokens
- Widest inputsQwen3.7 Flash and Kimi K2.7 Code HighspeedQwen3.7 Flash: Text, Images, Video · Kimi K2.7 Code Highspeed: Text, Images, Video · DeepSeek V4 Flash: Text
- Self-hostingKimi K2.7 Code Highspeed and DeepSeek V4 FlashPublishes downloadable weights
| Measure | Weight | Qwen3.7 Flash | Kimi K2.7 Code Highspeed | DeepSeek V4 Flash |
|---|---|---|---|---|
| Price | 50% | 100 | 25 | 86 |
| Inputs & features | 30% | 80 | 80 | 45 |
| Context window | 20% | 60 | 37 | 60 |
| Overall | 100% | 86/100 | 44/100 | 68/100 |
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 | Qwen3.7 FlashAlibaba (Qwen) | Kimi K2.7 Code HighspeedMoonshot AI | DeepSeek V4 FlashDeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 144.6 | — | 146.1 (best) |
| ECI rank | #80 of 148 | — | #71 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 82.3% | — | — |
| FrontierMath Tiers 1–3Research-level mathematics | 19.3% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 86.7% | — | — |
| Price per million tokens | |||
| Input | $0.03 (best) | $1.90 | $0.14 |
| Output | $0.13 (best) | $8.00 | $0.28 |
| Cached input | $0.003 | — | — |
| Blended (3:1) | $0.055 (best) | $3.42 | $0.175 |
| Long-context rate | Over 32K: $0.10 / $0.40 | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 11 providers | Median of 42 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 131,072 tokens | 262,144 tokens | 384,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | qwen3.7-flash | — | — |
| API providers | 12 | 11 | 48 (best) |
| Released | Jul 15, 2026 | Jun 12, 2026 | Apr 24, 2026 |
| Knowledge cutoff | — | Jan 2025 | May 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.7 Flash$0.56
- Kimi K2.7 Code Highspeed$35.00
- DeepSeek V4 Flash$1.96
Which should you choose?
Which is better: Qwen3.7 Flash, Kimi K2.7 Code Highspeed or DeepSeek V4 Flash?
Qwen3.7 Flash is the better all-round choice, scoring 86/100 against DeepSeek V4 Flash (68) and Kimi K2.7 Code Highspeed (44). 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, Qwen3.7 Flash, Kimi K2.7 Code Highspeed or DeepSeek V4 Flash?
Qwen3.7 Flash is cheaper at $0.03 input / $0.13 output per million tokens (official Alibaba API price). DeepSeek V4 Flash costs $0.14 input / $0.28 output per million tokens (median across 42 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 $0.055 per million tokens for Qwen3.7 Flash versus $0.175 for DeepSeek V4 Flash (3.2× as much) and $3.42 for Kimi K2.7 Code Highspeed (62× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.7 Flash has an ECI of 144.6, Kimi K2.7 Code Highspeed has not been scored yet and DeepSeek V4 Flash has an ECI of 146.1.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.7 Flash, Kimi K2.7 Code Highspeed and DeepSeek V4 Flash 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?
Qwen3.7 Flash and DeepSeek V4 Flash have the largest context windows (1,000,000 and 1,000,000 tokens), against 262,144 for Kimi K2.7 Code Highspeed. Maximum output per response: Qwen3.7 Flash up to 131,072, Kimi K2.7 Code Highspeed up to 262,144, DeepSeek V4 Flash up to 384,000 tokens.
Which can read images, PDFs, audio or video?
Qwen3.7 Flash accepts text, images and video; Kimi K2.7 Code Highspeed accepts text, images and video; DeepSeek V4 Flash accepts text. Qwen3.7 Flash handles the widest range of inputs.
Are any of these open source?
Kimi K2.7 Code Highspeed and DeepSeek V4 Flash publishes its weights and can be self-hosted; Qwen3.7 Flash is proprietary.
Which is newer?
Qwen3.7 Flash is the newest, released Jul 15, 2026. Kimi K2.7 Code Highspeed came out Jun 12, 2026; DeepSeek V4 Flash came out Apr 24, 2026. Knowledge cutoff: Kimi K2.7 Code Highspeed Jan 2025, DeepSeek V4 Flash May 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.
