moonshotai.kimi-k2.5
bedrock_converse · chat model
moonshotai.kimi-k2.5 is listed here as a chat model from bedrock_converse. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Input
$0.6000 / 1M tokens
Output
$3.0000 / 1M tokens
Cached input
N/A
Context
262.1K
Quick read
Best for
Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.
Things to verify
Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.
Pricing
| Item | Price |
|---|---|
| Input | $0.6000 / 1M tokens |
| Output | $3.0000 / 1M tokens |
| Embedding | $0.6000 / 1M tokens |
Token limits
Context window
262.1K
Max input tokens
262.1K
Max output tokens
262.1K
Max tokens
262.1K
Capabilities
| Capability | Supported |
|---|---|
| Vision | ✅ |
| Function calling | ✅ |
| Parallel function calling | — |
| Tool choice | ✅ |
| Prompt caching | — |
| Reasoning | — |
| Response schema | — |
| System messages | ✅ |
| Audio input | — |
| Audio output | — |
| Web search | — |
| PDF input | — |
| Video input | — |
Benchmarks
Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer
| Benchmark | Score | Metric | Scope | Checked | Source |
|---|---|---|---|---|---|
| GPQA Diamond | 87.6 | Score | Base model: Kimi-K2.5 (Kimi-K2.5) | 2026-05-31 | Link |
| LiveCodeBench v6 | 85.0 | Pass@1 | Base model: Kimi-K2.5 (Kimi-K2.5) | 2026-05-31 | Link |
| SWE-bench Pro | 50.7 | score | Base model: Kimi-K2.5 (Kimi-K2.5) | 2026-05-31 | Link |
| SWE-bench Verified | 70.8 * | score | Base model: Kimi-K2.5 (Kimi-K2.5) | 2026-05-31 | Link |
| Terminal-Bench 2.0 | 43.2 * | score | Base model: Kimi-K2.5 (Kimi-K2.5) | 2026-05-31 | Link |
| Apex Agents | 14.4 * | score | Base model: Kimi-K2.5 (Kimi-K2.5) | 2026-05-31 | Link |
| Artificial Analysis Intelligence Index | 46.8 | score | Base model: kimi-k2.5 (moonshotai/kimi-k2.5) | 2026-05-31 | Link |
| Artificial Analysis Coding Index | 39.6 | score | Base model: kimi-k2.5 (moonshotai/kimi-k2.5) | 2026-05-31 | Link |
| Artificial Analysis Agentic Index | 58.9 | score | Base model: kimi-k2.5 (moonshotai/kimi-k2.5) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
Docs
| Official docs |
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Comparing from
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| moonshotai.kimi-k2.5 bedrock_converse | In $0.6000 / 1M tokens Out $3.0000 / 1M tokens | imagetextvideo
Output: text | VisionFunction callingTool choiceSystem messages | 262.1K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| moonshotai.kimi-k2.5 Bedrock | In $0.6000 / 1M tokens Out $3.0000 / 1M tokens | imagetextvideo
Output: text | VisionFunction callingTool choiceSystem messages | 262.1K | Text + image covered Overall 92% |
| moonshotai.kimi-k2.5 Bedrock | In $0.6000 / 1M tokens Out $3.0000 / 1M tokens | imagetextvideo
Output: text | VisionFunction callingTool choiceSystem messages | 262.1K | Text + image covered Overall 92% |
| moonshotai.kimi-k2.5 Bedrock | In $0.6000 / 1M tokens Out $3.0000 / 1M tokens | imagetextvideo
Output: text | VisionFunction callingTool choiceSystem messages | 262.1K | Text + image covered Overall 92% |
| moonshotai.kimi-k2.5 Bedrock | In $0.7200 / 1M tokens Out $3.6000 / 1M tokens | imagetextvideo
Output: text | VisionFunction callingTool choiceSystem messages | 262.1K | Text + image covered Overall 89% |
| moonshotai.kimi-k2.5 Bedrock | In $0.7200 / 1M tokens Out $3.6000 / 1M tokens | imagetextvideo
Output: text | VisionFunction callingTool choiceSystem messages | 262.1K | Text + image covered Overall 89% |
| moonshotai.kimi-k2.5 Bedrock | In $0.7200 / 1M tokens Out $3.6000 / 1M tokens | imagetextvideo
Output: text | VisionFunction callingTool choiceSystem messages | 262.1K | Text + image covered Overall 89% |
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