Kimi K2.7 Code
aki-io/kimi-k2-7-code-1100b제공: aki-io · 패밀리: kimi-k2 · 출시 2026-06-12 · 지식 컷오프: 2025-01
⚠ 이 모델은 커뮤니티 파인튜닝 / 파생본으로, 벤더 공식 릴리스가 아닙니다.
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
기능
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding79
- Tool calling40/40
- Structured output20/20
- Reasoning10/10
- Context window (100K → 1M)8/20
- Provider availability1/10
Agents91
- Tool calling35/35
- Structured output25/25
- Reasoning15/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output82
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control0/10
- Price-friendly for high-volume12/20
Cost efficiency48
- Headline price (log-scaled)48/95
- Has prompt-cache pricing0/5
Long context61
- Context window (100K → 2M)51/90
- Has published price for full window10/10
Vision82
- Accepts image input50/50
- Context window (10K → 1M)21/30
- Has published price10/10
- Provider availability1/10
Production-readiness50
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)0/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $5.80 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $11.60 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $3.22 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $9.88 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $12.12 $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
가격 상세
추천 가격 제공자: aki-io · kimi-k2.7-code-1100b
1곳 제공사에서 이용 가능
| 제공자 | 제공자 모델 ID | 입력 / 1M | 출력 / 1M | 컨텍스트 | 출시일 |
|---|---|---|---|---|---|
| AKI.IO aki-io | kimi-k2.7-code-1100b | $0.860 | $3.00 | 262K | 2026-06-12 |
Frequently asked questions
How much does Kimi K2.7 Code cost?
Kimi K2.7 Code costs $0.860 per 1M input tokens and $3.00 per 1M output tokens, sourced from aki-io. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Kimi K2.7 Code?
Kimi K2.7 Code has a context window of 262K tokens, with a max output of 82K tokens per reply. This is the total combined size of prompt + completion.
Does Kimi K2.7 Code support tool calling?
Yes. Kimi K2.7 Code supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Kimi K2.7 Code support structured output / JSON mode?
Yes. Kimi K2.7 Code supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can Kimi K2.7 Code accept image input?
Yes. Kimi K2.7 Code accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check aki-io's docs for the exact rule.
Is Kimi K2.7 Code open-weight?
Yes. Kimi K2.7 Code's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Kimi K2.7 Code?
If Kimi K2.7 Code doesn't fit, consider GPT OSS 120B. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More aki-io models
- GPT OSS 120B$0.15 in / $0.55 out
Capability lists this model is in
마지막 업데이트:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.