ByteDance/Seed-2.0-pro vs moonshotai/Kimi-K2.5
Side-by-side comparison of ByteDance/Seed-2.0-pro and moonshotai/Kimi-K2.5: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API.
ByteDance/Seed-2.0-pro
Input / 1M
$0.50
Output / 1M
$3.00
Context
256K
Model ID
deepinfra/ByteDance/Seed-2.0-pro
moonshotai/Kimi-K2.5
Input / 1M
$0.45
Output / 1M
$2.25
Context
262K
Model ID
deepinfra/moonshotai/Kimi-K2.5
Pricing & specifications
| ByteDance/Seed-2.0-pro | moonshotai/Kimi-K2.5 | |
|---|---|---|
| Input price / 1M | $0.50 | $0.45 |
| Output price / 1M | $3.00 | $2.25 |
| Context window | 256K tokens | 262K tokens |
| Max output | N/A | 131K tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | DeepInfra | DeepInfra |
Questions people ask
Is ByteDance/Seed-2.0-pro better than moonshotai/Kimi-K2.5?
Benchmark data is limited for one or both models. Compare pricing and capabilities in the tables above, and test both on your own workload.
Which is cheaper, ByteDance/Seed-2.0-pro or moonshotai/Kimi-K2.5?
moonshotai/Kimi-K2.5 is cheaper. ByteDance/Seed-2.0-pro costs $0.50/$3.00 per 1M input/output tokens, while moonshotai/Kimi-K2.5 costs $0.45/$2.25.
Can I use ByteDance/Seed-2.0-pro and moonshotai/Kimi-K2.5 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "deepinfra/ByteDance/Seed-2.0-pro" and "deepinfra/moonshotai/Kimi-K2.5", no other code changes needed.
What are the context windows?
ByteDance/Seed-2.0-pro supports up to 256K tokens of context. moonshotai/Kimi-K2.5 supports up to 262K tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.
Switch between ByteDance/Seed-2.0-pro and moonshotai/Kimi-K2.5 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.