Omni Fast
谷歌的多模态人工智能技术允许你通过对话动态编辑视频（例如交换物体、更改风格），同时保持场景的连贯性。
- Starting price
- Per Request
- Context
- —
- Maximum input window
- Modalities
- →
Pricing by Supplier
Capabilities / Supported modalities
Provider & data privacy
o200k_basePerformance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·Omni Fast
This model is not included in the current benchmark snapshot.
Missing models or measurements are not zero scores.
Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.
About Omni Fast
谷歌的多模态人工智能技术允许你通过对话动态编辑视频（例如交换物体、更改风格），同时保持场景的连贯性。
Use cases and prompting
Starting points for evaluation; supported inputs and options are listed in API access.
Use cases to explore
- Explore product storyboards and short promotional scenes.
- Prototype camera movement and scene pacing before a full production.
Practical tips
Describe the subject, action, camera movement and lighting. Test a short scene first; check the API documentation for supported duration, resolution and reference inputs.
Example prompt
A ceramic cup on a wooden table at sunrise. Steam rises slowly as the camera moves closer. Warm side lighting, a quiet background, one continuous shot.
API access
Code samples
/v1/chat/completions| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| 标准按次 | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about omni-fast
What is omni-fast?
谷歌的多模态人工智能技术允许你通过对话动态编辑视频（例如交换物体、更改风格），同时保持场景的连贯性。
How do I call omni-fast?
Create an API key with access to omni-fast, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is omni-fast priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
How should I evaluate omni-fast for my project?
Describe the subject, action, camera movement and lighting. Test a short scene first; check the API documentation for supported duration, resolution and reference inputs.