DeepSeek V4 Flash vs Kimi K2.7 Code Highspeed vs Qwen3.7 Flash
Qwen3.7 Flash comes out ahead, 86 to 68 and 44 on our weighted score, and it is the cheaper option too.
DeepSeekDeepSeek V4 Flash
68/100- ECI146.1
- Price$0.14 / $0.28
- Context1M
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
- Our pick
Alibaba (Qwen)Qwen3.7 Flash
86/100- ECI144.6
- Price$0.03 / $0.13
- 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 contextDeepSeek V4 Flash and Qwen3.7 FlashDeepSeek V4 Flash 1,000,000 · Qwen3.7 Flash 1,000,000 · Kimi K2.7 Code Highspeed 262,144 tokens
- Widest inputsKimi K2.7 Code Highspeed and Qwen3.7 FlashDeepSeek V4 Flash: Text · Kimi K2.7 Code Highspeed: Text, Images, Video · Qwen3.7 Flash: Text, Images, Video
- Self-hostingDeepSeek V4 Flash and Kimi K2.7 Code HighspeedPublishes downloadable weights
| Measure | Weight | DeepSeek V4 Flash | Kimi K2.7 Code Highspeed | Qwen3.7 Flash |
|---|---|---|---|---|
| Price | 50% | 86 | 25 | 100 |
| Inputs & features | 30% | 45 | 80 | 80 |
| Context window | 20% | 60 | 37 | 60 |
| Overall | 100% | 68/100 | 44/100 | 86/100 |
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 | DeepSeek V4 FlashDeepSeek | Kimi K2.7 Code HighspeedMoonshot AI | Qwen3.7 FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 146.1 (best) | — | 144.6 |
| ECI rank | #71 of 148 (best) | — | #80 of 148 |
| 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 | $0.14 | $1.90 | $0.03 (best) |
| Output | $0.28 | $8.00 | $0.13 (best) |
| Cached input | — | — | $0.003 |
| Blended (3:1) | $0.175 | $3.42 | $0.055 (best) |
| Long-context rate | Same rate | Same rate | Over 32K: $0.10 / $0.40 |
| Price source | Median of 42 providers | Median of 11 providers | Official Alibaba API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 384,000 tokens (best) | 262,144 tokens | 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 | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | — | qwen3.7-flash |
| API providers | 48 (best) | 11 | 12 |
| Released | Apr 24, 2026 | Jun 12, 2026 | Jul 15, 2026 |
| Knowledge cutoff | May 2025 | 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.
- DeepSeek V4 Flash$1.96
- Kimi K2.7 Code Highspeed$35.00
- Qwen3.7 Flash$0.56
Which should you choose?
Which is better: DeepSeek V4 Flash, Kimi K2.7 Code Highspeed or Qwen3.7 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, DeepSeek V4 Flash, Kimi K2.7 Code Highspeed or Qwen3.7 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. DeepSeek V4 Flash has an ECI of 146.1, Kimi K2.7 Code Highspeed has not been scored yet and Qwen3.7 Flash has an ECI of 144.6.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4 Flash, Kimi K2.7 Code Highspeed and Qwen3.7 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?
DeepSeek V4 Flash and Qwen3.7 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: DeepSeek V4 Flash up to 384,000, Kimi K2.7 Code Highspeed up to 262,144, Qwen3.7 Flash up to 131,072 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4 Flash accepts text; Kimi K2.7 Code Highspeed accepts text, images and video; Qwen3.7 Flash accepts text, images and video. Kimi K2.7 Code Highspeed handles the widest range of inputs.
Are any of these open source?
DeepSeek V4 Flash and Kimi K2.7 Code Highspeed 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: DeepSeek V4 Flash May 2025, 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.
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