← Models

Kimi K3 vs Claude Fable 5.1

Compare Kimi K3 from Moonshot AI and Claude Fable 5.1 from Anthropic on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

Moonshot AIKimi K3AnthropicClaude Fable 5.1
Moonshot AI logo
Kimi K3
Moonshot AI · text, image, video → text

Kimi K3 is Kimi’s flagship model for long-horizon coding and end-to-end knowledge work, with a 1M-token context window and industry-leading intelligence.

Input$2.84 /M
Output$14.2 /M
Cache read$0.284 /M
Anthropic logo
Claude Fable 5.1
Anthropic · text, image, pdf → text

Claude-fable-5-1 is Anthropic's most capable newly released model, suitable for the most demanding reasoning and long-running agent work. Claude Fable 5.1, while keeping input and output prices the same as Claude Fable 5, reduces cache read prices to one quarter of the original and is more capable for long-running agent programming, multi-step research, and document, spreadsheet, and slide processing. (The model is extremely expensive and not recommended for casual use.)

Input$11 /M
Output$55 /M
Cache read$0.275 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

Kimi K3
Claude Fable 5.1
Input /M
$2.84
$11
Output /M
$14.2
$55
Cache read /M
$0.284
$0.275
Context length
1,048,576
1,000,000
Max output
1,048,576
128,000
Time to First Token
0.7 s
86.5 s
Throughput
73.1 tok/s
65.2 tok/s
Modalities
textimagevideo
textimagepdf
Supported Parameters
thinkingfunction callingstructured outputs
thinkingtoolsfunction callingstructured outputs
API Formats
chat_completions · claude_api
Released
July 16, 2026
September 2, 2026

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

kimi-k3claude-fable-5-1

Tokens / day

-

Requests / day

-

Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

kimi-k3claude-fable-5-1

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

-

LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
kimi-k3claude-fable-5-1
1460148015001520
Overall
14871502
WebDev Arena
kimi-k3claude-fable-5-1
1640168017201760
Overall
16551743

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

Kimi K3
$383 /mo
Claude Fable 5.1
$1,485 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: Kimi K3, Claude Fable 5.1?

Kimi K3: $14.2/M output tokens; Claude Fable 5.1: $55/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

Kimi K3: 0.7s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

Kimi K3 accepts 1,048,576 and Claude Fable 5.1 accepts 1,000,000 input tokens. Maximum output per request is 1,048,576 tokens on Kimi K3 and 128,000 tokens on Claude Fable 5.1.

Which one generates tokens faster?

Kimi K3 at 73.1 tok/s and Claude Fable 5.1 at 65.2 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

Kimi K3 accepts text, image and video input and supports thinking, function calling and structured outputs; Claude Fable 5.1 accepts text, image and PDF input and supports thinking, tool calling, function calling and structured outputs.

Can I call Kimi K3 and Claude Fable 5.1 with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

Popular comparisons

Related model match-ups readers also look at.