Morph V3 Fast
Morph V3 Fast applies code edit suggestions from frontier models to your source files at high throughput. It supports 81.9K tokens input and 16.4K tokens output. On AI Gateway, pay $0.8 per million input tokens and $1.2 per million output tokens.
View API reference- Input and output price
- Input $0.80, Output $1.20, Per 1M tokens
- 24h uptime
- Loading AI Gateway uptime
import { streamText } from 'ai'
const result = streamText({ model: 'morph/morph-v3-fast', prompt: 'Why is the sky blue?'})Copy link to headingPlayground
Try out Morph V3 Fast by Morph. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.
Morph V3 Fast
Copy link to headingProviders
Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.
| Provider |
|---|
Copy link to headingUptime24 hours
Direct request success rate on AI Gateway and per-provider. Visit the docs for more info.
Copy link to headingThroughput24 hours
P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the docs for more info.
Copy link to headingLatency24 hours
P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the docs for more info.
Getting started
Call Morph V3 Fast through AI Gateway with the AI SDK generateText and streamText functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider.
Install the AI SDK (pnpm add ai dotenv), create an API key from the API Keys page, and set it as AI_GATEWAY_API_KEY in your environment. Full setup is covered in the text generation quickstart.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'morph/morph-v3-fast', prompt: 'Why is the sky blue?', });
console.log(result.text);}
main().catch(console.error);Top-level parameters
The same Morph V3 Fast request in each API format AI Gateway supports.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'morph/morph-v3-fast', system: 'You are a concise technical assistant.', prompt: 'Summarize the tradeoffs between static generation and SSR.', maxOutputTokens: 1024, temperature: 0.5, });
console.log(result.text);}
main().catch(console.error);Standard parameters like prompt, messages, temperature, and tools work as documented in the AI SDK docs. These are the parameters with model-specific behavior.
| Parameter | Type | Required | Description |
|---|---|---|---|
model | string | Yes | Model ID in the form creator/model, e.g. morph/morph-v3-fast. AI Gateway routes the request to an available provider. |
maxOutputTokens | number | No | Hard cap on generated tokens. Morph V3 Fast supports up to 16,384 output tokens. |
providerOptions | Record<string, JSONValue> | No | AI Gateway routing options under gateway, plus any provider-native options under the provider’s own namespace — see the table below. |
Input limits
| Input | Formats | Sources | Max count | Max size | Limits |
|---|---|---|---|---|---|
| Text | — | — | — | — | Prompt and response share the 82K-token context window |
Provider options
Set AI Gateway routing options under providerOptions.gateway. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK.
Learn more in the AI SDK provider docs.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'morph/morph-v3-fast', prompt: 'Why is the sky blue?', providerOptions: { gateway: { only: ['morph'], }, }, });
console.log(result.text);}
main().catch(console.error);These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example providerOptions.anthropic) exactly as documented by the AI SDK.
| Parameter | Type | Required | Description |
|---|---|---|---|
providerOptions.gateway.only | string[] | No | Restrict routing to these provider slugs. Requests fail over only within the listed providers. |
providerOptions.gateway.order | string[] | No | Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks. |
providerOptions.gateway.sort | 'cost' | 'ttft' | 'tps' | No | Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order. |
providerOptions.gateway.zeroDataRetention | boolean | No | Route only to providers with a zero-data-retention policy for this model. |
Routing across providers
AI Gateway serves the same model through multiple providers and fails over automatically. order expresses a preference while keeping every provider eligible; only is a hard allowlist — if none of the listed providers are available the request fails instead of falling back.
Options under a provider's own namespace (for example providerOptions.anthropic) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside gateway routing options.
Copy link to headingAbout Morph V3 Fast
You send the original file, an edit snippet with // ... existing code ... markers, and an optional instruction. You get back the merged file.
Live throughput metrics appear on this page. Each edit uses on the order of 700 to 1,400 tokens, compared to 3,500 to 4,500 for a frontier model rewriting the whole file. The context window is 81.9K tokens; max output is 16.4K tokens.
Routine edits merge reliably: parameter additions, function body swaps, line insertions, and deletions. Harder cases, like logic redistribution across scopes or edits buried in duplicated structures, belong to the heavier variant or Morph's auto router.
``
Planning model --> edit snippet --> v3 Fast --> merged file --> disk
``
Any planning model that outputs lazy edit snippets works. Many tools use the same // ... existing code ... pattern. Drop v3 Fast into the file-write step. Your planning model stays the bottleneck, not the merge. Product details and benchmarks appear on https://morphllm.com/.
Copy link to headingWhat To Consider When Choosing a Provider
- Configuration: This is a merge tool, not an assistant. Place it between your planning model and the filesystem.
- Zero Data Retention: Zero Data Retention is available for this model. It is offered on a per-provider and model basis. See the documentation for details.
- Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
Copy link to headingWhen to Use Morph V3 Fast
Best for
- Routine edit merges: Single-function changes, parameter additions, body replacements, and line-level insertions or deletions
- Streaming coding UIs: Users watch edits land and expect fast visual feedback
- High-volume batch runs: Per-edit cost and duration directly affect margin
Consider alternatives when
- Repeated merge failures: Route problematic edit patterns to the heavier variant
- Automatic routing preference: Morph's
automode handles complexity-based triage - General-purpose coding needs: You need a full coding model, not a merge primitive
Copy link to headingConclusion
Default to v3 Fast and escalate the rare failures. The merge step rarely sits on the critical path.
Copy link to headingFrequently Asked Questions
What goes in, what comes out?
You get the merged source file. Send the original file in
<code>tags, an edit snippet in<update>tags with// ... existing code ...markers, and an optional<instruction>. The API follows the OpenAI Chat Completions format.How does deletion work?
v3 Fast treats omitted sections as removal. Leave a section out of the edit snippet and don't add a
// ... existing code ...marker there.What planning models pair well?
Any model that emits lazy edit snippets. The marker pattern isn't proprietary, and mainstream code-generation models already produce it.
Will I hit the context limit?
Unlikely for typical files. The window is 81.9K tokens, so even large single files rarely approach it.
How do I know an edit needs the heavier variant?
Route when merges are wrong. Typical triggers include multi-scope refactors, edits inside heavily repeated patterns, and logic redistribution across functions. Keep v3 Fast as the default otherwise.
Where does the merge sit in the coding-agent pipeline?
The merge step usually finishes before your planning model returns its next chunk. The bottleneck stays upstream, not in the merge.
Where are list prices for this model?
Current rates appear on this page. AI Gateway tracks live pricing across each provider that serves the model.