claude-sonnet-4-5 vs kimi-k2
Side-by-side comparison of claude-sonnet-4-5 and kimi-k2— benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API.
claude-sonnet-4-5
Input / 1M
$3.00
Output / 1M
$15.00
Context
1M
Model ID
anthropic/claude-sonnet-4-5
kimi-k2
Input / 1M
$0.60
Output / 1M
$2.50
Context
262K
Model ID
vertex/kimi-k2
Benchmark comparison
Intelligence Indexreasoning
claude-sonnet-4-5—
kimi-k240.9%
Coding Indexcoding
claude-sonnet-4-5—
kimi-k234.8%
Math Indexmath
claude-sonnet-4-5—
kimi-k294.7%
GPQA Diamondreasoning
claude-sonnet-4-5—
kimi-k283.8%
AIME 2025math
claude-sonnet-4-5—
kimi-k294.7%
LiveCodeBenchcoding
claude-sonnet-4-5—
kimi-k285.3%
Terminal-Bench Hardagentic
claude-sonnet-4-5—
kimi-k231.1%
τ²-Benchagentic
claude-sonnet-4-5—
kimi-k293.0%
SciCodecoding
claude-sonnet-4-5—
kimi-k242.4%
MMLU Proknowledge
claude-sonnet-4-5—
kimi-k284.8%
Humanity's Last Examreasoning
claude-sonnet-4-5—
kimi-k222.3%
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
| claude-sonnet-4-5 | kimi-k2 | |
|---|---|---|
| Input price / 1M | $3.00 | $0.60 |
| Output price / 1M | $15.00 | $2.50 |
| Context window | 1M tokens | 262K tokens |
| Max output | 64K tokens | 262K tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | Yes | — |
| Provider | Anthropic PBC | Google LLC (Vertex AI) |
Questions people ask
Is claude-sonnet-4-5 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 — claude-sonnet-4-5 or kimi-k2?
kimi-k2 is cheaper. claude-sonnet-4-5 costs $3.00/$15.00 per 1M input/output tokens, while kimi-k2 costs $0.60/$2.50.
Can I use claude-sonnet-4-5 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 — "anthropic/claude-sonnet-4-5" or "vertex/kimi-k2" — no other code changes needed.
What are the context windows?
claude-sonnet-4-5 supports up to 1M 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 claude-sonnet-4-5 and kimi-k2 with one line of code
Requesty provides a single OpenAI-compatible API for 400+ models. Change the model parameter, not your code.
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