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Kimi K2 Instruct 0905

moonshotai/kimi-k2-instruct-0905

Par Moonshot AI · famille: kimi · sorti 2025-09-05 · fin de connaissance: 2024-10

$0.390
Entrée / 1M jetons
$1.90
Sortie / 1M jetons
262K
Fenêtre de contexte
16K
Sortie max

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

Capacités

Tool callingRaisonnementSortie structuréePièces jointesPoids ouvertsContrôle de température
Modalités: entrée text · sortie text

Model fit scores

0–100 · higher is better

These 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.

Coding78
  • Tool calling40/40
  • Structured output20/20
  • Reasoning0/10
  • Context window (100K → 1M)8/20
  • Provider availability10/10
Agents80
  • Tool calling35/35
  • Structured output25/25
  • Reasoning0/15
  • Output token limit10/15
  • Provider availability10/10
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.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$2.90
< $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
$5.80
< $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
$1.73
< $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
$5.02
< $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
$5.82
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

Détail des tarifs

Tarif recommandé de io-net · moonshotai/Kimi-K2-Instruct-0905

$0.390
Entrée
$1.90
Sortie
$0.195
Lecture cache
$0.780
Écriture cache

Fournisseur le moins cher : nvidia · Unknown entrée + Unknown sortie

Disponible chez 11 fournisseurs

FournisseurID modèle fournisseurEntrée / 1MSortie / 1MContextePublié le
Groq
groq
moonshotai/kimi-k2-instruct-0905$1.00$3.00262K2025-09-05
Deep Infra
deepinfra
moonshotai/Kimi-K2-Instruct-0905$0.400$2.00262K2025-09-05
Hugging Face
huggingface
moonshotai/Kimi-K2-Instruct-0905$1.00$3.00262K2025-09-04
NanoGPT
nano-gpt
moonshotai/Kimi-K2-Instruct-0905$0.400$2.00256K2025-09-25
SiliconFlow (China)
siliconflow-cn
Pro/moonshotai/Kimi-K2-Instruct-0905$0.400$2.00262K2025-09-08
SiliconFlow (China)
siliconflow-cn
moonshotai/Kimi-K2-Instruct-0905$0.400$2.00262K2025-09-08
IO.NET
io-net
moonshotai/Kimi-K2-Instruct-0905$0.390$1.9033K2024-09-05
Baseten
baseten
moonshotai/Kimi-K2-Instruct-0905$0.600$2.50262K2025-09-05
Synthetic
synthetic
hf:moonshotai/Kimi-K2-Instruct-0905$1.20$1.20262K2025-09-05
Nvidia
nvidia
moonshotai/kimi-k2-instruct-0905UnknownUnknown262K2025-09-05
SiliconFlow
siliconflow
moonshotai/Kimi-K2-Instruct-0905$0.400$2.00262K2025-09-08

Incohérences de données entre fournisseurs

  • context_window varies: 256000, 262000, 262144, 32768
  • release_date varies (span 385d): 2024-09-05, 2025-09-04, 2025-09-05, 2025-09-08, 2025-09-25

Les fournisseurs rapportent des valeurs différentes pour ce modèle. Les infos clés ci-dessus utilisent un fournisseur représentatif ; voir le tableau pour le détail par fournisseur.

Frequently asked questions

How much does Kimi K2 Instruct 0905 cost?

Kimi K2 Instruct 0905 costs $0.390 per 1M input tokens and $1.90 per 1M output tokens, sourced from io-net. 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.

More Moonshot AI models

Dernière mise à jour :

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.