Head-to-head comparison
DeepSeek V4.1 Flash (DeepSeek) and Kimi K2.7 Code (Moonshot AI) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.
Snapshot as of 15 September 2026
As of 15 September 2026, DeepSeek V4.1 Flash holds the stronger ModelCap Index position (#21 vs #55); DeepSeek V4.1 Flash is 5.8× cheaper per output token ($0.60/1M vs $3.50/1M); DeepSeek V4.1 Flash offers the longer context window (1M vs 262K tokens); and DeepSeek V4.1 Flash ships open weights.
Evidence: 2 public benchmark observations across 2 boards · 2 public benchmark observations across 2 boards. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.
Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.
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DeepSeek V4.1 Flash ranks higher on the ModelCap Index as of 15 September 2026: #21 against #55. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
DeepSeek V4.1 Flash is cheaper on output tokens: $0.60/1M against $3.50/1M. Input tokens are $0.15/1M for DeepSeek V4.1 Flash and $0.71/1M for Kimi K2.7 Code. Prices are the lowest listed API offer ModelCap observed, in USD per million tokens. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.60 for DeepSeek V4.1 Flash versus $3.17 for Kimi K2.7 Code. DeepSeek V4.1 Flash costs 81.1% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
DeepSeek V4.1 Flash has the larger context window: 1M tokens against 262K.
The two models do not share a coding benchmark board on ModelCap yet, so no head-to-head coding score is published; the ModelCap Index position is the closest overall signal.
DeepSeek V4.1 Flash: Open weights. Kimi K2.7 Code: Restricted license. Open weights mean the checkpoint can be downloaded and self-hosted under its licence; API-only models are available solely through hosted endpoints.
ModelCap currently lists 17 API providers for DeepSeek V4.1 Flash and 14 for Kimi K2.7 Code, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.
Every figure comes from the sealed ModelCap dataset published 15 September 2026; the page re-renders within a minute of each data refresh, and the ModelCap Index positions are the same ones shown on the live rankings.