claude-sonnet-5 vs kimi-k3
Side-by-side comparison of claude-sonnet-5 and kimi-k3: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. kimi-k3 outperforms claude-sonnet-5 on 5 of 5 shared benchmarks.
claude-sonnet-5
Input / 1M
$2.00
Output / 1M
$10.00
Context
1M
Model ID
anthropic/claude-sonnet-5
kimi-k3
Input / 1M
$3.00
Output / 1M
$15.00
Context
1.0M
Model ID
moonshot/kimi-k3
Benchmark comparison
Intelligence Indexreasoning
claude-sonnet-545.1%
kimi-k350.2%
Coding Indexcoding
claude-sonnet-571.5%
kimi-k376.2%
GPQA Diamondreasoning
claude-sonnet-591.1%
kimi-k393.5%
SciCodecoding
claude-sonnet-554.3%
kimi-k359.5%
Humanity's Last Examreasoning
claude-sonnet-541.3%
kimi-k346.9%
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-5 | kimi-k3 | |
|---|---|---|
| Input price / 1M | $2.00 | $3.00 |
| Output price / 1M | $10.00 | $15.00 |
| Context window | 1M tokens | 1.0M tokens |
| Max output | 128K tokens | 1.0M tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | Yes | N/A |
| Provider | Anthropic PBC | Moonshot AI |
Questions people ask
Is claude-sonnet-5 better than kimi-k3?
kimi-k3 outperforms claude-sonnet-5 on 5 of 5 shared benchmarks. See the benchmark comparison above for specifics: claude-sonnet-5 and kimi-k3 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, claude-sonnet-5 or kimi-k3?
claude-sonnet-5 is cheaper. claude-sonnet-5 costs $2.00/$10.00 per 1M input/output tokens, while kimi-k3 costs $3.00/$15.00.
Can I use claude-sonnet-5 and kimi-k3 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "anthropic/claude-sonnet-5" and "moonshot/kimi-k3", no other code changes needed.
What are the context windows?
claude-sonnet-5 supports up to 1M tokens of context. kimi-k3 supports up to 1.0M 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-5 and kimi-k3 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.