Moonshot AI has 2 models in The AI Leaderboard directory: Kimi K3, Kimi K2.6. This provider hub compares their verified availability, licensing, context windows, pricing references and intended uses, with direct links to every model guide.
Quick answer: Kimi K3 is Moonshot AI's highest-ranked model here at #6 with an Overall score of 79.2. Use the lineup table below to compare it with the provider’s other current, specialist, open-weight or migration-reference models.
Moonshot AI model lineup at a glance
Metric | Current directory value |
|---|---|
Models covered | 2 |
Currently ranked | 1 |
Open-weight models | 2 |
Restricted models | 0 |
Legacy or migration references | 0 |
Highest-ranked model | Kimi K3, #6, Overall 79.2 |
Last verified | September 2, 2026 |
Complete Moonshot AI model directory
Model names in this table link directly to their complete guides. Status and pricing can change, so confirm the active endpoint and provider terms before procurement or migration.
Model | Status | License | Context | Best fit |
|---|---|---|---|---|
Available; open weights | Open weights | 1M tokens | Open-weight frontier work, coding, research and self-hosting | |
Available | Open weights with hosted API access | 256,000 tokens | fast question answering, coding, multimodal understanding and agent tool use |
How the Moonshot AI models differ
Model | Directory role | Modalities | Maximum output | Access |
|---|---|---|---|---|
Kimi K3 | Open weights | Text, image and video input; text output | Not specified in launch documentation | See the guide for current access routes |
Kimi K2.6 | Open weights | Text, image and video input; text output | Model and endpoint specific | Kimi app, Kimi API and downloadable model resources |
The labels above describe access and lifecycle, not a hidden capability ranking. Only 1 Moonshot AI model in the current top eight receive a rank on this site. Other guides remain unranked until comparable evidence is available.
Moonshot AI model pricing
Model | Pricing reference | Cost caveat |
|---|---|---|
Kimi K3 | $3 cache-miss input / $15 output per million tokens | Self-hosting still incurs infrastructure and operations costs |
Kimi K2.6 | Self-hosting cost varies; check Kimi Platform for current hosted API rates | Self-hosting still incurs infrastructure and operations costs |
Token price is not cost per accepted result. Measure retries, tool calls, latency, infrastructure and reviewer time on the same task set.
Which Moonshot AI model should you choose?
Requirement | Starting point | Why |
|---|---|---|
Highest current rank | Kimi K3 | Highest Moonshot AI placement in the current top eight |
Open weights or self-hosting | Kimi K3, Kimi K2.6 | Review the exact license, checkpoint and hardware needs |
Restricted specialist work | No restricted model in this provider directory | Use generally available models and least-privilege controls |
Migration or reproduction | Kimi K2.6 | Compare current versions using pinned snapshots |
Lowest operational cost | Measure two or three eligible models | Headline token prices omit retries, tools, caching and human review |
Moonshot AI models, explained
Kimi K3
Kimi K3 was released July 17, 2026. It is listed as available; open weights with open weights. The documented context window is 1M tokens, and the maximum output is Not specified in launch documentation.
- Best fit: Open-weight frontier work, coding, research and self-hosting.
- Modalities: Text, image and video input; text output.
- Access: See the guide for current access routes.
- Pricing reference: $3 cache-miss input / $15 output per million tokens.
- Current ranking: #6 with an Overall score of 79.2.
Read the complete Kimi K3 guide for benchmarks, limitations, official sources and an evaluation framework.
Kimi K2.6
Kimi K2.6 was released 2026. It is listed as available with open weights with hosted api access. The documented context window is 256,000 tokens, and the maximum output is Model and endpoint specific.
- Best fit: fast question answering, coding, multimodal understanding and agent tool use.
- Modalities: Text, image and video input; text output.
- Access: Kimi app, Kimi API and downloadable model resources.
- Pricing reference: Self-hosting cost varies; check Kimi Platform for current hosted API rates.
Read the complete Kimi K2.6 guide for benchmarks, limitations, official sources and an evaluation framework.
How to evaluate Moonshot AI models
Shortlist the Moonshot AI models that meet your access, licensing and modality requirements. Freeze 20 to 50 representative tasks, then give each candidate the same prompts, tools, context, reasoning budget and retry limits. Record the exact model identifier because provider aliases can change.
Measure | Record | Decision use |
|---|---|---|
Task completion | Pass rate and rubric score | Establish whether the model meets the acceptance threshold |
Reliability | Repeated-run variance and recovery behavior | Avoid choosing from one lucky result |
Quality | Factuality, instruction following and reviewer acceptance | Separate polished output from correct output |
Tool use | Wrong calls, retries, permission errors and unsafe actions | Evaluate the model and agent harness together |
Efficiency | Wall time, tokens, caching, tools and review labor | Calculate cost per accepted result |
Governance | Retention, training, regional processing and audit logs | Confirm the deployment fits policy requirements |
Availability, versions and lifecycle
Moonshot AI may expose different snapshots, effort settings, products and partner integrations under similar labels. Treat every model name as incomplete without an exact endpoint or checkpoint. Re-run regression tests after any model, system prompt, retrieval, tool or permission change.
- Available means a documented access route exists, not that every region or account has access.
- Preview models can change behavior, price or retirement dates before general availability.
- Open weights require an exact license and checkpoint review; “open” does not guarantee open training data or low operating cost.
- Restricted models require separate eligibility, safeguards and data-handling review.
- Legacy models remain useful for migration and reproduction but should not be the default for a new deployment.
Sources and update policy
Official Moonshot AI model documentation is the provider-level starting point. Each linked model guide cites its own first-party launch page, model card, pricing reference and safety documentation.
Compare this provider with the complete Best AI Models directory.
Last verified September 2, 2026. The hub should be updated when the provider launches, retires, renames or reprices a model, changes context or output limits, alters licensing, or modifies regional availability.
Frequently asked questions
How many Moonshot AI models are covered?
This hub covers 2: Kimi K3, Kimi K2.6. Every model has a dedicated guide linked from the directory table and profile sections.
What is the best Moonshot AI model?
Kimi K3 is Moonshot AI's highest-ranked model in the current AI Leaderboard, at number 6 with an Overall score of 79.2. Workload-specific testing can still favor another model.
Does Moonshot AI offer open weights?
Yes. The directory identifies Kimi K3, Kimi K2.6 as open-weight options. Review the exact license, downloadable artifact and serving requirements before deployment.
How current is the pricing?
Pricing references were verified September 2, 2026 from first-party documentation summarized in each model guide. Always recheck the provider before budgeting because cache, batch, long-context, tool and regional rates can change.
Should every Moonshot AI model be tested?
No. Remove models that fail access, license, modality, context, latency or governance requirements first. Test the smallest credible shortlist on representative work.