DeepSeek V3.2 (Chat) vs Kimi K2.5
Complete pricing and performance comparison between DeepSeek's DeepSeek V3.2 (Chat) and Moonshot's Kimi K2.5.
Quick Verdict
Cheaper
DeepSeek V3.2 (Chat)
2.1x cheaper input, 7.1x cheaper output
Larger Context
DeepSeek V3.2 (Chat)
128K vs 128K
Higher Quality
Kimi K2.5
Score: 47 vs 32
Faster
DeepSeek V3.2 (Chat)
34 vs 33 tok/s
Pricing Comparison
| Spec | DeepSeek V3.2 (Chat) | Kimi K2.5 | Difference |
|---|---|---|---|
| Provider | DeepSeek | Moonshot | |
| Input / 1M tokens | $0.28 | $0.6 | DeepSeek V3.2 (Chat) is 53% more expensive |
| Output / 1M tokens | $0.42 | $3 | DeepSeek V3.2 (Chat) is 86% more expensive |
| Context Window | 128K | 128K | Same |
| Max Output | 8K | 33K |
Performance Benchmarks
| Metric | DeepSeek V3.2 (Chat) | Kimi K2.5 | Winner |
|---|---|---|---|
| Quality Index | 32 | 47 | Kimi K2.5 |
| Output Speed | 34 tok/s | 33 tok/s | DeepSeek V3.2 (Chat) |
| Time to First Token | 1.50s | 1.30s | Kimi K2.5 |
| Value (Quality/$) | 114.6 | 78.0 | Higher = better value |
Benchmark data from Artificial Analysis. Quality Index is a composite score across reasoning, coding, and knowledge tasks.
Cost at Scale
Estimated cost at different usage levels (3:1 input-to-output token ratio, typical for chat).
| Usage | DeepSeek V3.2 (Chat) | Kimi K2.5 | Savings |
|---|---|---|---|
Single request 1K in / 300 out | $0.0004 | $0.0015 | DeepSeek V3.2 (Chat) saves $0.0011 |
10 requests 10K in / 3K out | $0.0041 | $0.015 | DeepSeek V3.2 (Chat) saves $0.011 |
100 requests 100K in / 30K out | $0.041 | $0.150 | DeepSeek V3.2 (Chat) saves $0.109 |
1,000 requests 1M in / 300K out | $0.406 | $1.50 | DeepSeek V3.2 (Chat) saves $1.09 |
10,000 requests 10M in / 3M out | $4.06 | $15.00 | DeepSeek V3.2 (Chat) saves $10.94 |
1M requests/mo 1B in / 300M out | $406.00 | $1500.00 | DeepSeek V3.2 (Chat) saves $1094.00 |
Pros & Cons
DeepSeek V3.2 (Chat) Strengths
- +Cheaper input tokens
- +Cheaper output tokens
- +Faster output (34 vs 33 tok/s)
Kimi K2.5 Strengths
- +Higher max output tokens
- +Higher quality score (47 vs 32)
- +Lower latency (faster first token)
When to Use Each Model
Choose DeepSeek V3.2 (Chat) for
- →Budget-conscious projects where cost is the primary factor
- →Real-time applications, chat, or autocomplete
Choose Kimi K2.5 for
- →Generating long-form content or detailed code
- →Tasks requiring maximum accuracy and reasoning
Frequently Asked Questions
Which is cheaper, DeepSeek V3.2 (Chat) or Kimi K2.5?
For input tokens, DeepSeek V3.2 (Chat) is 2.1x cheaper at $0.28/1M tokens. For output tokens, DeepSeek V3.2 (Chat) is 7.1x cheaper at $0.42/1M tokens. At typical usage (1M input + 300K output), DeepSeek V3.2 (Chat) costs $0.406 vs Kimi K2.5 at $1.50.
What's the context window difference?
DeepSeek V3.2 (Chat) supports 128K context (128,000 tokens), while Kimi K2.5 supports 128K (128,000 tokens). Kimi K2.5 can handle 1x more context in a single request.
Which model has better benchmarks?
Quality Index: DeepSeek V3.2 (Chat) scores 32 vs Kimi K2.5 at 47. Speed: DeepSeek V3.2 (Chat) generates 34 tok/s vs Kimi K2.5 at 33 tok/s. Time to first token: DeepSeek V3.2 (Chat) at 1.50s vs Kimi K2.5 at 1.30s.
When should I choose DeepSeek V3.2 (Chat) over Kimi K2.5?
Choose DeepSeek V3.2 (Chat) when you need: Cheaper input tokens, Cheaper output tokens, Faster output (34 vs 33 tok/s). Choose Kimi K2.5 when you need: Higher max output tokens, Higher quality score (47 vs 32), Lower latency (faster first token).
How much would 10,000 API requests cost?
At 1K input + 300 output tokens per request (typical chat): DeepSeek V3.2 (Chat) = $4.06, Kimi K2.5 = $15.00. At 10K input + 1K output per request (longer conversations): DeepSeek V3.2 (Chat) = $32.20, Kimi K2.5 = $90.00.
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