Kimi vs Claude: Pricing, Models & When to Use Each
Kimi and Claude both aim at agentic work, from different directions. Moonshot ships open-weight K2 models — a swarm-oriented generalist and a coding specialist — alongside K3; Anthropic's Claude lineup covers Haiku through Fable. Here is every model from both families on ATP, with prices, capabilities, documented context, and a calculator that prices the same workload on each.
Kimi models on ATP
Claude models on ATP
Lowest Kimi price
Lowest Claude price
Models & prices
Every Kimi and Claude model ATP serves today. Rates are USD per 1M tokens (USD 1 = 100 credits); the bar shows each model's output rate against the most expensive model on this page.
Kimi· Moonshot (Kimi)
Input $3.00 · Output $15.00 / 1M tokens
Input $0.95 · Output $4.00 / 1M tokens
Input $0.95 · Output $4.00 / 1M tokens
Claude· Anthropic
Input $10.00 · Output $50.00 / 1M tokens
Input $5.00 · Output $25.00 / 1M tokens
Input $5.00 · Output $25.00 / 1M tokens
Input $5.00 · Output $25.00 / 1M tokens
Input $3.00 · Output $15.00 / 1M tokens
Input $3.00 · Output $15.00 / 1M tokens
Input $1.00 · Output $5.00 / 1M tokens
- —: not published by the vendor.
Same workload, every model
Set the traffic once; every model on this page is priced at its current ATP price. No discounts are assumed.
Workload
Applied only to models with a cache-read price.
Monthly cost at current prices
| Model | Per month |
|---|---|
Kimi K2.6Kimi | $580.00Lowest on this page |
Kimi K2.7 CodeKimi | $580.00 |
Claude Haiku 4.5Claude | $650.00 |
Kimi K3Kimi | $1,950.00 |
Claude Sonnet 5Claude | $1,950.00 |
Claude Sonnet 4.6Claude | $1,950.00 |
Claude Opus 5Claude | $3,250.00 |
Claude Opus 4.8Claude | $3,250.00 |
Claude Opus 4.7Claude | $3,250.00 |
Claude Fable 5Claude | $6,500.00 |
USD prices · estimate only · the cache share applies only to models with a cache-read price
Lowest on this page: Kimi K2.6 $580.00
When to pick which
Where each family tends to fit, based on what the vendors document. Facts beyond our prices are cited under Sources.
Pick Kimi for
- Swarm-style agents that fan work out in parallel. Moonshot reports Kimi K2.6 runs scaling to 300 sub-agents executing 4,000 coordinated steps.
- Long-horizon coding agents on an open-weight model: Kimi K2.7 Code is Moonshot's coding build on K2.6, with thinking always on over a 256K context; Moonshot reports 62.0 on Kimi Code Bench v2 versus 50.9 for K2.6 (vendor-reported).
- Teams that want an open-weight option in the fleet: K2.6 and K2.7 Code are released under a Modified MIT license, so the same model can also be self-hosted later.
- Fast text-plus-tools calls: ATP exposes K2.6 without thinking, matching Moonshot's instant mode.
Pick Claude for
- Agentic coding that needs a 1M-token window: Anthropic documents 1M context for Sonnet 5, Sonnet 4.6, Opus 4.7, Opus 4.8 and Fable 5.
- Image and screenshot input inside agent runs — ATP's catalog lists vision on every Claude model here.
- Computer use — driving browsers, terminals and real software — a documented focus of Sonnet 4.6, Sonnet 5 and Opus 4.8.
- Repeated-prefix agent loops: Claude lists both cache-read and cache-write (5-minute and 1-hour) rates on ATP, so long shared context gets cheaper on hits.
Use both under one key
You rarely have to choose just one. On ATP both families sit behind one endpoint and one project key — so you can route each task to the model that fits and still keep one budget, one allowlist and one log.
- One project key — spend and revocation bound to one project
- Model allowlist — only the ids you enable can be called; others return 403
- Project budget — credits are allocated down org → workspace → project, so the allocation is the cap
- Per-request logs and one bill — model, key, project and credits for every call, across both vendors
from openai import OpenAI
# one project key; both ids must be on the project's allowlist
client = OpenAI(base_url="https://api.atptoken.ai/v1", api_key="atp-•••")
def ask(model, prompt):
r = client.chat.completions.create(
model=model, messages=[{"role": "user", "content": prompt}]
)
return r.choices[0].message.content
draft = ask("kimi-k2.7-code", "Summarize this ticket…")
final = ask("claude-sonnet-5", "Review: " + draft)
# both calls: same log, same credit balance, same budgetOrganization Northwind Labs · 9,842 credits Workspace Product 62% support-bot models: kimi-k2.7-code, claude-sonnet-5 38% web-app models: gpt-5.5, deepseek-v4-flash Workspace Media lab 100% video-lab limit reached models: seedance-2-0, kling-v3-pro
Questions teams ask
FAQ
- Which is cheaper, Kimi or Claude?
- At ATP prices (USD per 1M tokens), Kimi runs from $0.95 / $4.00 on kimi-k2.6 to $3.00 / $15.00 on kimi-k3; Claude runs from $1.00 / $5.00 on claude-haiku-4-5 to $10.00 / $50.00 on claude-fable-5. Which one costs less for you depends on your input/output mix and which tier you need — the calculator on this page prices the same workload on every model.
- Which has the longer context window, Kimi or Claude?
- Documented context windows — Kimi: Kimi K2.6 262K. Claude: Claude Opus 5 1M, Claude Opus 4.8 1M, Claude Opus 4.7 1M, Claude Sonnet 5 1M, Claude Haiku 4.5 200K. —: not published by the vendor.
- Is Kimi open source?
- Kimi K2.6 and K2.7 Code are open-weight: Moonshot publishes the weights on Hugging Face under a Modified MIT license. On ATP you call them as hosted APIs with a project key, the same way you call Claude — no infrastructure to run.
- Can I use Kimi and Claude with one API key?
- Yes. On ATP both families sit behind the same OpenAI-compatible endpoint (https://api.atptoken.ai/v1), and Anthropic-format clients can use /v1/messages. One project key calls any model on that project's allowlist; every request lands in the same per-request log and debits the same credit balance.
- How do I keep a team on the models we approved?
- Use the project's model allowlist: enable only the model ids you approved, and calls to any other id are refused with 403. Give the project its own credit allocation so the budget is the ceiling, and review spend per model in the per-request logs.
Where the claims come from
Rates, capabilities and context on this page come from the ATP model catalog. Other claims cite the sources below.
Other comparisons
- textDeepSeek vs ClaudeVolume-priced V4 vs Anthropic's Haiku-to-Fable lineup — rates, context, same-workload cost.
- textQwen vs DeepSeekAlibaba's Max / Plus / Flash tiers vs DeepSeek V4 — tiered vs flat pricing, context, same-workload cost.
- textGemini vs GPTGoogle's Pro / Flash / Flash-Lite vs OpenAI's GPT-5.4 to 5.6 tiers — rates, context, same-workload cost.
- videoKling vs SeedanceSame prompts, real outputs side by side — plus per-second rates for every Kling and Seedance tier.
Try both on one key — start with USD 5.
Issue a project key, allowlist the models you want to test, and compare them on your own traffic.