Phi-4-mini-reasoning is a lightweight open model designed for advanced mathematical reasoning and logic-intensive problem-solving. It is particularly well-suited for tasks such as formal proofs, symbolic computation, and solving multi-step word problems. With its efficient architecture, the model balances high-quality reasoning performance with cost-effective deployment, making it ideal for educational applications, embedded tutoring, and lightweight edge or mobile systems. Phi-4-mini-reasoning supports a 128K token context length, enabling it to process and reason over long mathematical problems and proofs. Built on synthetic and high-quality math datasets, the model leverages advanced fine-tuning techniques such as supervised fine-tuning and preference modeling to enhance reasoning capabilities. Its training incorporates safety and alignment protocols, ensuring robust and reliable performance across supported use cases.
AIHubMix Phi 4 Mini (reasoning) vs Kimi K3
Compare AIHubMix Phi 4 Mini (reasoning) from Microsoft and Kimi K3 from Moonshot AI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
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.
Pricing & Specifications
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
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.
Tokens / day
Requests / day
Performance Past 3 Days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (tok/s)
TTFT (s)
Uptime (%)
LMArena Benchmarks
LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.
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.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: AIHubMix Phi 4 Mini (reasoning), Kimi K3?
AIHubMix Phi 4 Mini (reasoning): $0.12/M output tokens; Kimi K3: $13.5/M. Use the cost calculator above to estimate your own workload.
How do their coding arena scores compare?
Kimi K3: 1531; AIHubMix Phi 4 Mini (reasoning): 1306 (LMArena coding leaderboard).
How large is each context window?
AIHubMix Phi 4 Mini (reasoning) accepts 128,000 and Kimi K3 accepts 1,048,576 input tokens. Maximum output per request is 4,000 tokens on AIHubMix Phi 4 Mini (reasoning) and 1,048,576 tokens on Kimi K3.
What inputs and capabilities does each model support?
AIHubMix Phi 4 Mini (reasoning) accepts text input; Kimi K3 accepts text, image and video input and supports thinking, function calling and structured outputs.
Can I call AIHubMix Phi 4 Mini (reasoning) 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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