Kimi K2 Instruct 0905
moonshotai/kimi-k2-0905من Moonshot AI · العائلة: kimi · أُصدِر 2025-09-05 · تاريخ المعرفة: 2024-10
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
القدرات
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.
Coding77
- Tool calling40/40
- Structured output20/20
- Reasoning0/10
- Context window (100K → 1M)8/20
- Provider availability9/10
Agents79
- Tool calling35/35
- Structured output25/25
- Reasoning0/15
- Output token limit10/15
- Provider availability9/10
JSON / structured output95
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume15/20
Cost efficiency58
- Headline price (log-scaled)53/95
- Has prompt-cache pricing5/5
Long context61
- Context window (100K → 2M)51/90
- Has published price for full window10/10
Production-readiness96
- Number of independent providers40/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers6/10
- Official model (not derivative)15/15
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 | $3.00 < $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 | $6.00 < $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 | $1.80 < $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 | $5.20 < $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 | $6.00 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
تفاصيل التسعير
السعر المُوصى به من kilo · moonshotai/kimi-k2-0905
أرخص مزود: iflowcn · Unknown إدخال + Unknown إخراج
متاح لدى 9 مزود
| المزود | معرف نموذج المزود | إدخال / 1M | إخراج / 1M | السياق | تاريخ الإصدار |
|---|---|---|---|---|---|
| OpenRouter openrouter | moonshotai/kimi-k2-0905 | $0.600 | $2.50 | 262K | 2025-09-05 |
| Vercel AI Gateway vercel | moonshotai/kimi-k2-0905 | $0.600 | $2.50 | 131K | 2025-09-05 |
| Jiekou.AI jiekou | moonshotai/kimi-k2-0905 | $0.600 | $2.50 | 262K | 2026-01 |
| iFlow iflowcn | kimi-k2-0905 | Unknown | Unknown | 256K | 2025-09-05 |
| ZenMux zenmux | moonshotai/kimi-k2-0905 | $0.600 | $2.50 | 262K | 2025-09-04 |
| NovitaAI novita-ai | moonshotai/kimi-k2-0905 | $0.600 | $2.50 | 262K | 2025-09-05 |
| Qiniu qiniu-ai | moonshotai/kimi-k2-0905 | Unknown | Unknown | 256K | 2025-09-08 |
| Kilo Gateway kilo | moonshotai/kimi-k2-0905 | $0.400 | $2.00 | 131K | 2025-09-05 |
| Helicone helicone | kimi-k2-0905 | $0.500 | $2.00 | 262K | 2025-09-05 |
اختلافات في بيانات المزودين
- context_window varies: 131072, 256000, 262000, 262144
- release_date varies (span 119d): 2025-09-04, 2025-09-05, 2025-09-08, 2026-01
يبلِّغ المزودون قيمًا مختلفة لهذا النموذج. تستخدم الحقائق السريعة أعلاه مزودًا تمثيليًا؛ راجع الجدول للتفاصيل لكل مزود.
Frequently asked questions
How much does Kimi K2 Instruct 0905 cost?
Kimi K2 Instruct 0905 costs $0.400 per 1M input tokens and $2.00 per 1M output tokens, sourced from kilo. 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 Instruct 0905?
Kimi K2 Instruct 0905 has a context window of 262K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.
Does Kimi K2 Instruct 0905 support tool calling?
Yes. Kimi K2 Instruct 0905 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 Instruct 0905 support structured output / JSON mode?
Yes. Kimi K2 Instruct 0905 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 Instruct 0905 accept image input?
No. Kimi K2 Instruct 0905 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Kimi K2 Instruct 0905 open-weight?
Yes. Kimi K2 Instruct 0905'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 Instruct 0905?
If Kimi K2 Instruct 0905 doesn't fit, consider Kimi K2.5, Kimi K2 Thinking, Kimi K2.6. 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 come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More Moonshot AI models
- Kimi K2.5$0.60 in / $3.00 out
- Kimi K2 Thinking$0.60 in / $2.50 out
- Kimi K2.6$0.95 in / $4.00 out
- Kimi K2 Instruct$0.10 in / $2.00 out
- Kimi K2 Instruct 0905$0.39 in / $1.90 out
Capability lists this model is in
آخر تحديث:
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.