ByteDance/Seed-2.0-pro vs kimi-k2
Side-by-side comparison of ByteDance/Seed-2.0-pro and kimi-k2: 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
kimi-k2
Input / 1M
$0.60
Output / 1M
$2.50
Context
262K
Model ID
vertex/kimi-k2
Benchmark comparison
Intelligence Indexreasoning
ByteDance/Seed-2.0-proN/A
kimi-k225.9%
Math Indexmath
ByteDance/Seed-2.0-proN/A
kimi-k294.7%
GPQA Diamondreasoning
ByteDance/Seed-2.0-proN/A
kimi-k283.8%
AIME 2025math
ByteDance/Seed-2.0-proN/A
kimi-k294.7%
LiveCodeBenchcoding
ByteDance/Seed-2.0-proN/A
kimi-k285.3%
Terminal-Bench Hardagentic
ByteDance/Seed-2.0-proN/A
kimi-k231.1%
τ²-Benchagentic
ByteDance/Seed-2.0-proN/A
kimi-k293.0%
MMLU Proknowledge
ByteDance/Seed-2.0-proN/A
kimi-k284.8%
Humanity's Last Examreasoning
ByteDance/Seed-2.0-proN/A
kimi-k223.8%
Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.
Pricing & specifications
| ByteDance/Seed-2.0-pro | kimi-k2 | |
|---|---|---|
| Input price / 1M | $0.50 | $0.60 |
| Output price / 1M | $3.00 | $2.50 |
| Context window | 256K tokens | 262K tokens |
| Max output | N/A | 262K tokens |
| Vision input | Yes | N/A |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | DeepInfra Inc. | Google LLC (Vertex AI) |
Questions people ask
Is ByteDance/Seed-2.0-pro better than kimi-k2?
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 kimi-k2?
kimi-k2 is cheaper. ByteDance/Seed-2.0-pro costs $0.50/$3.00 per 1M input/output tokens, while kimi-k2 costs $0.60/$2.50.
Can I use ByteDance/Seed-2.0-pro and kimi-k2 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 "vertex/kimi-k2", no other code changes needed.
What are the context windows?
ByteDance/Seed-2.0-pro supports up to 256K tokens of context. kimi-k2 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 kimi-k2 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.