Tasks and inputs
Kimi K3 is listed for Image-text-to-text, Text generation, Video-text-to-text. It accepts text, image, video and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Kimi K3 from Moonshot AI: Multimodal Kimi model with 1M context and toggleable max-effort thinking for long-horizon agent work.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
The current Kimi K3 API guide permits max_completion_tokens up to 1,048,576, with 131,072 the default. It always reasons, using low, high or max effort. Preserve the complete assistant message through tool loops. Vision input uses base64 or uploaded-file references rather than public image URLs. Cache writes have separate 5-minute and 1-hour TTL charges; cached input hits do not add another write charge.
Keep the hosted model ID separate from a downloadable checkpoint name. A local serving engine can expose a different subset of tool, visual and structured-output features from the first-party service. Replay the application’s message history and tool results with the exact interface and reasoning settings you intend to use.
A documented context or output allowance describes capacity, rather than accuracy on a particular task. Include prompts, retained reasoning, tool definitions and tool results when budgeting a long interaction. Use the selected route’s current billing unit and account terms; an absent price is not a claim of free usage. Check migration behavior before replacing a pinned model or relying on a moving alias.
Build a small evaluation set from the work your application actually handles. Include incomplete information, contradictory inputs and a case that should stop for clarification. Define an acceptable deliverable before running the model, then inspect failures as carefully as successful examples. Keep input material, tools and effort settings consistent when comparing candidates.
Record the exact model identifier, deployment route and request settings with each result. Count complete runs, including rejected outputs, retries and tool calls. When the workflow creates files or code, open the files or execute the existing checks before accepting the result. A plausible first response can hide an incomplete final deliverable.
The specifications describe supported interfaces and request capacity. They do not establish a measured quality ranking or a latency guarantee for your account. SyncDev has not independently benchmarked this model. Choose a deployment after testing the languages, input formats and operating conditions that matter to your users.
Explore moonshotai models, browse model tasks, or compare two models with the same acceptance criteria.
Compare the model on the work you need to complete.
Kimi K3 is listed for Image-text-to-text, Text generation, Video-text-to-text. It accepts text, image, video and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 1.05M context and 1.05M maximum output. The listed route charges $3.00 input and $15.00 output per million tokens. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
The weights are downloadable under the publisher’s model licence. Check runtime support and size the complete model and working context for your expected concurrency.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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