Sulat.com
AI models
$10 off the fastest DeepSeek V4.1 Flash, Kimi K3 and GLM 5.3 from Synthetic
Requesty logo

Model details

Kimi K2.7 Code (EU)

Kimi K2.7 Code (EU) is a coding-specialised branch of Moonshot AI’s open-weights Kimi K2 family, positioned as a successor in a lineage focused on practical developer assistance. Both third-party aggregators describe it as the same model identity routed through a European endpoint, with weights published on Hugging Face so teams can self-host or route through gateways of their choice. The cutoff knowledge base and the 262,144-token context window frame it for working across sizeable codebases and documentation, while multimodel text, image, and video input give it room to read mixed repository artefacts alongside source files.

In day-to-day use the model is pitched at long-horizon repository tasks where extended multi-step planning is common, and the “less overthinking” framing suggests it tries to keep agent loops efficient rather than padding traces. Tool calling and structured output let it slot into editor agents and CI-style pipelines, and the expanded 262,144-token output ceiling supports sizeable code generation and refactoring passes in a single turn. Pricing dispersion across gateways — from sub-dollar input rates up to the Requesty reference tier — means practical fit depends heavily on routing choice, so the EU endpoint is best seen as a latency-and-residency option for European teams that want open weights without running their own inference stack.

Requestykimi-k2.7-code@eukimi-k2

Quick Info

Powered by
Provider
Requesty
Model key
kimi-k2.7-code@eu
Release date
Jun 12, 2026
Last updated
Jun 12, 2026
Knowledge cutoff
2025-01
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$1.25
Output token cost
$4.50

Limits

Output tokens
262,144 tokens
Context window
262,144 tokens

Latest news about Kimi K2.7 Code (EU)

Requesty

CoverageRelease Notes

A follow-up GitHub changelog post dated July 7, 2026 confirms that Kimi K2.7 Code is now additionally available on Copilot Business and Copilot Enterprise plans, expanding beyond the initial Pro, Pro+, and Max rollout announced on July 1, 2026. As before, the model is described as an open-weight coding model hosted by The post reiterates that Kimi K2.7 Code is off by default for Copilot Business and Enterprise, requiring administrators to enable the Kimi K2.7 Code policy in Copilot settings before anyone in the organization can select it. GitHub recommends administrators review open-weight models against their own security, complian

Requesty

CoverageRelease Notes

GitHub announced on July 1, 2026 that Kimi K2.7 Code, an open-weight model from Moonshot AI, is now generally available in GitHub Copilot. It is described as the first open-weight model offered as a selectable option in the Copilot model picker, positioned as a lower-cost option for coding workflows. The model is hoste Rollout began for Copilot Pro, Pro+, and Max plans, with availability extending to Visual Studio Code (1.127.0+), Visual Studio (17.14.6+), Copilot CLI, the Copilot cloud agent, the Copilot App, github.com, GitHub Mobile (iOS/Android), JetBrains (1.9.1-251+), Xcode, and Eclipse. The post notes that Copilot Business and

Requesty

Coverage

SQ Magazine reports that Moonshot AI has launched Kimi K2.7 Code, a new open source coding model, in an article published June 15, 2026. The piece frames K2.7 Code as promising stronger software development performance while using significantly fewer reasoning tokens compared with prior approaches. The article is positioned as a launch overview from a technology publication and summarizes the model's coding focus without providing new technical specifications or benchmark data. Creator attribution to Moonshot AI is preserved in the page excerpt.

Requesty

CoverageBenchmark

Inferbase's catalog page documents Kimi K2.7 Code as a coding-focused chat model developed by Moonshot AI, using a Mixture-of-Experts architecture with 384 experts, a 262,144-token context window, and approximately 1,026.9 billion parameters. The page lists a maximum output of 16,384 tokens and a release date of June 1 Reported benchmark scores include HLE 35.0%, AA-LCR 79.3%, GPQA 89.6%, Tau2-Bench 63.1%, IFBench 47.8%, SciCode 20.2%, Tau2 Banking 60.8, Terminal-Bench Hard 67.4%, and Terminal-Bench 2.1 43.8, with an overall Intelligence index of 44.7% and a Coding index of 26.3. The page also provides INT8 GPU sizing estimates at up

Requesty

CoverageBenchmark

BenchLM's Kimi Code Bench v2 leaderboard, verified September 10, 2026, lists Kimi K2.7 Code by Moonshot AI as an open-weight model with a 256K context window and an overall score of 62.0% (65.49 overall) on the benchmark, placing it second behind the closed Kimi K3 at 72.9%. The leaderboard page describes Kimi Code Ben The benchmark is refreshed quarterly and BenchLM considers it a display-only reference in its current freshness state, with the public benchmark set remaining available. The page records 37 confirmed releases in the 30 days preceding September 10, 2026 and tracks 489 destinations across 435 benchmarks, providing proven

Videos about Kimi K2.7 Code (EU)

More models around Kimi K2.7 Code (EU)