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gemini-2.5-flash-lite-nothink vs Kimi K3

Output tokens cost $0.40 per million on gemini-2.5-flash-lite-nothink and $15.00 per million on Kimi K3. Input tokens cost $0.10 per million on gemini-2.5-flash-lite-nothink and $3.00 per million on Kimi K3. Cached input tokens are billed at $0.01 per million on gemini-2.5-flash-lite-nothink and $0.30 per million on Kimi K3. Context lengths are 1,048,576 tokens on gemini-2.5-flash-lite-nothink and 1,048,576 tokens on Kimi K3. Time to first token (TTFT) measured on AIHubMix is 0.9s on gemini-2.5-flash-lite-nothink and 0.9s on Kimi K3. Measured output throughput is 237.4 tok/s on gemini-2.5-flash-lite-nothink and 73.1 tok/s on Kimi K3.

Googlegemini-2.5-flash-lite-nothinkMoonshot AIKimi K3
+ Add model · 2/4
Google logo
gemini-2.5-flash-lite-nothink
Google · text, image, audio, video → text

Gemini 2.5 Flash-Lite is a balanced model from Google, optimized for applications that require low-latency performance. It retains the practical capabilities of the Gemini 2.5 family, including configurable reasoning based on budget, integration with tools such as grounding via Google Search and code execution, multimodal input support, and an ultra-long context window of up to 1 million tokens, delivering a strong balance between efficiency, functionality, and cost.

Input$0.10 /M
Output$0.40 /M
Details
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$3.00 /M
Output$15.00 /M
Details

Pricing & Specifications

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

gemini-2.5-flash-lite-nothink
Kimi K3
Input /M
$0.10
$3.00
Output /M
$0.40
$15.00
Cache read /M
$0.01
$0.30
Context length
1,048,576
1,048,576
Max output
65,536
1,048,576
Time to First Token
0.9 s
0.9 s
Throughput
237.4 tok/s
73.1 tok/s
Modalities
textimageaudiovideo
textimagevideo
Supported Parameters
toolsfunction callingstructured outputslong context
thinkingfunction callingstructured outputs
API Formats
Released
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-

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.

gemini-2.5-flash-lite-nothinkkimi-k3

Tokens / day

-

Requests / day

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Performance Past 3 Days

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

gemini-2.5-flash-lite-nothinkkimi-k3

Throughput (tok/s)

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TTFT (s)

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Uptime (%)

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Cost calculator

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

gemini-2.5-flash-lite-nothink
$12.00 /mo
Kimi K3
$405 /mo

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

FAQ

Which is cheaper: gemini-2.5-flash-lite-nothink, Kimi K3?

gemini-2.5-flash-lite-nothink: $0.40/M output tokens; Kimi K3: $15.00/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

gemini-2.5-flash-lite-nothink: 0.9s 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?

gemini-2.5-flash-lite-nothink accepts 1,048,576 and Kimi K3 accepts 1,048,576 input tokens. Maximum output per request is 65,536 tokens on gemini-2.5-flash-lite-nothink and 1,048,576 tokens on Kimi K3.

Which one generates tokens faster?

gemini-2.5-flash-lite-nothink at 237.4 tok/s and Kimi K3 at 73.1 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

gemini-2.5-flash-lite-nothink accepts text, image, audio and video input and supports tool calling, function calling, structured outputs and long context; Kimi K3 accepts text, image and video input and supports thinking, function calling and structured outputs.

Can I call gemini-2.5-flash-lite-nothink and Kimi K3 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.

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