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Kimi K2.7 Code (batch)

Released at: June 12, 2026

API StatusAvailable for integration
Context Window262,144 tokens✓ verified today
Input Price / MTok$0.47✓ verified today
Output Price / MTok$2.00✓ verified today

Model Overview

Moonshot AI · Active Model

  • Long-Context
  • API Available
  • Vetted Benchmarks
  • Production Ready

Kimi K2.7 Code (batch) by Moonshot AI — Technical Architecture, Empirical Benchmarks & API Specs

1. Executive Summary & Core Positioning§

Kimi K2.7 Code (batch) is an advanced artificial intelligence model engineered by Moonshot AI. Tailored for complex multi-step reasoning, programming synthesis, and extended document comprehension, Kimi K2.7 Code (batch) represents a key architectural iteration in the Moonshot AI model family. First released in 2026-06-12, it serves enterprise developers, research teams, and autonomous system architects requiring strict instruction compliance.

Featuring an input capacity of 262,144 tokens (approximately 350 words), Kimi K2.7 Code (batch) processes multi-file code repositories, lengthy technical reports, and complex prompts in a single inference call.


2. Technical Architecture & Verified Specifications§

Official specification breakdown for Kimi K2.7 Code (batch) based on verified provider metadata:

  • Model Name: Kimi K2.7 Code (batch)
  • Developer / Provider: Moonshot AI
  • Context Window Capacity: 262,144 tokens (~350 words)
  • Modality Support: Text, Code
  • API Availability: Available via API Gateway
  • Tool-Calling Accuracy Score: Pending Empirical Benchmark
  • Time to First Token (TTFT): Varies by Host Provider

3. Benchmark Evaluations & Performance Metrics§

Kimi K2.7 Code (batch) undergoes standardized evaluation across key industry benchmark suites:

  • MMLU (Massive Multitask Language Understanding): Evaluates multi-subject knowledge across STEM, humanities, and social sciences.
  • HumanEval & SWE-bench: Assesses functional Python code synthesis and real-world software engineering bug resolution.
  • GSM8K & MATH: Tests multi-step arithmetic reasoning and formal mathematical proof construction.
  • Chatbot Arena ELO: Evaluates human preference, instruction following, and conversational quality against rival models.

4. Developer API & Integration Specs§

Programmatic integration for Kimi K2.7 Code (batch) follows standard OpenAI-compatible REST endpoints.

import os
import requests

api_key = os.getenv("MODEL_API_KEY")
url = "https://openrouter.ai/api/v1/chat/completions"

headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

payload = {
    "model": "kimi-k2-7-code-batch",
    "messages": [
        {"role": "system", "content": "You are a senior software architect and AI system evaluator."},
        {"role": "user", "content": "Analyze system architecture bottlenecks and suggest refactoring strategies."}
    ],
    "temperature": 0.1,
    "max_tokens": 2048
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

5. Production Use Cases & Deployment Scenarios§

5.1 Autonomous Agents & Tool Execution§

Given its instruction compliance and tool-calling capabilities (Pending Empirical Benchmark), Kimi K2.7 Code (batch) is frequently integrated as the reasoning engine for autonomous software agents, browser automation pipelines, and API orchestrators.

5.2 Enterprise Document Synthesis§

With its 262,144 tokens input capacity, engineering and legal teams process full regulatory filings, annual corporate disclosures, and technical documentation directly without context loss.

5.3 Programmatic Code Generation§

Development teams utilize Kimi K2.7 Code (batch) for automated code generation, pull request audits, unit test suite creation, and language migration (e.g. Python to Rust).


6. Token Economics & Pricing Breakdown§

Inference pricing per million tokens for Kimi K2.7 Code (batch):

  • Input Token Cost: $0.47 per MTok
  • Output Token Cost: $2.00 per MTok
  • Prompt Caching Discounts: Supported on selected API providers (up to 50% savings on repeated prompt prefixes)
  • Batch Processing: Available for non-latency-sensitive bulk inference workloads

7. Comparative Specification Matrix§

Metric / Parameter**Kimi K2.7 Code (batch)**Provider Ecosystem Baseline
DeveloperMoonshot AIIndustry Average
Context Window262,144 tokens128,000 tokens
Input Price / MTok$0.47Variable
Output Price / MTok$2.00Variable
API AccessSupportedStandard

8. Frequently Asked Questions (FAQ)§

Q: What is Kimi K2.7 Code (batch)'s context window limit?§

A: Kimi K2.7 Code (batch) supports an input context window of 262,144 tokens.

Q: What is the API pricing for Kimi K2.7 Code (batch)?§

A: Kimi K2.7 Code (batch) is priced at $0.47 per million input tokens and $2.00 per million output tokens.

Q: Is Kimi K2.7 Code (batch) accessible via API?§

A: Yes, Kimi K2.7 Code (batch) is available for programmatic integration.

Developer
Moonshot AI✓ verified today
Release Date
June 12, 2026✓ verified today
Context Window
262,144 tokens350 words✓ verified today
API Access
Publicly AvailableIntegrate via official API✓ verified today
Input Cost
$0.47per million tokens✓ verified today
Output Cost
$2.00per million tokens✓ verified today
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Vetted Benchmarks

MMLU(estimated)Score: 80.4% (Top 58%)
HumanEval(estimated)Score: 90.6% (Top 28%)
MATH(estimated)Score: 55.8% (Top 55%)
MT-Bench(estimated)Score: 8.6 (Top 54%)
GPQA(estimated)Score: 41.2% (Top 50%)
HellaSwag(estimated)Score: 83.4% (Top 53%)

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Originally published on llmdb.app

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