Morph V3 Large API262K context
Morph's high-accuracy apply model for complex code edits.
Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).
What is Morph V3 Large?
Morph's high-accuracy apply model for complex code edits. ~4,500 tokens/sec with 98% accuracy for precise code transformations. The model requires the prompt to be in the following format: <instruction>{instruction}</instruction> <code>{initial_code}</code>...
Morph V3 Large pricing
Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):
| Model | Input / 1M | Output / 1M | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| Morph V3 Large | $0.90 | $1.90 | — | — | 262K |
On output price, Morph V3 Large is cheaper than 47% of the 309 models in the catalog.
What Morph V3 Large costs per month
| Workload | Tokens in / out (monthly) | Est. cost |
|---|---|---|
| Support chatbot | 40M / 12M | $58.80 |
| RAG / knowledge base | 200M / 20M | $218 |
| Coding agent | 80M / 25M | $120 |
| Batch extraction | 150M / 8M | $150 |
| Content generation | 20M / 40M | $94.00 |
Estimate your own monthly cost
Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.
Morph V3 Large vs alternatives
| Model | Input / 1M | Output / 1M | Context | Our test |
|---|---|---|---|---|
| Morph V3 Large | $0.90 | $1.90 | 262K | — |
| Morph V3 Fast | $0.80 | $1.20 | 82K | — |
| GLM 5 | $0.60 | $1.92 | 203K | — |
| Qwen3.6 Plus | $0.33 | $1.95 | 1M | — |
| Qwen3 235B A22B | $0.45 | $1.82 | 131K | — |
When not to use Morph V3 Large
- It is served by a single provider, so there is less failover headroom during an outage.
Specs
| Model ID | morph/morph-v3-large |
| Modality | text->text (input: text) |
| Context window | 262,144 tokens |
| Max output | 131,072 tokens |
| Tool / function calling | — |
| Structured output (JSON) | ✅ Yes |
| Released | 2025-07-07 |
| Open weights | — (hosted API only) |
How to call Morph V3 Large
from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
model="morph/morph-v3-large",
messages=[{"role": "user", "content": "Hello"}],
)
print(resp.choices[0].message.content)curl https://api.datallmlab.com/v1/chat/completions \
-H "Authorization: Bearer YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"morph/morph-v3-large","messages":[{"role":"user","content":"Hello"}]}'import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
model: "morph/morph-v3-large",
messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);The same key routes Morph V3 Large and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.
Prompting tips for Morph V3 Large
- Be explicit and show the shape of the answer. Spell out format, tone and constraints up front, and include one short example of the output you want — Morph V3 Large follows concrete instructions better than abstract ones.
- Huge 262K context — but anchor the ask. You can paste whole documents or codebases; models attend most to the start and end, so put the key instruction at the top and restate it after long inputs.
- Constrain JSON with a schema. Use
response_format/ structured outputs rather than "reply in JSON" to get valid, parseable objects every time.
Tips are derived from Morph V3 Large's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.
Open-source tools for Morph V3 Large
Popular open-source frameworks and agents to build with Morph V3 Large over the API — star counts pulled from GitHub (July 2026).
Listed by GitHub stars; inclusion is by ecosystem relevance (agent frameworks, SDKs and gateways), not affiliation. Stars change — see each repo for current numbers.
Migrating to Morph V3 Large
Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → morph/morph-v3-large. Messages, streaming and the rest of your code stay the same. Routing & failover guide.
Rate limits & reliability
Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.
Related reading
Call Morph V3 Large with one key
300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.
Get an API keyCompare pricingFrequently asked questions
What is Morph V3 Large?
Morph's high-accuracy apply model for complex code edits. It accepts text input with a 262K-token context window and was released on 2025-07-07. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.
How much does Morph V3 Large cost?
On DataLLM Lab it is $0.90 per 1M input tokens and $1.90 per 1M output tokens — cheaper than about 47% of the 309-model catalog on output price. Pay-as-you-go, no subscription.
What is the context window of Morph V3 Large?
262K tokens, with up to 131K max output tokens.
Is Morph V3 Large open source?
No open weights are published — it is available through hosted API access only.
How do I call the Morph V3 Large API?
Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "morph/morph-v3-large". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.
What are good alternatives to Morph V3 Large?
Close options by price and capability include Morph V3 Fast, GLM 5, Qwen3.6 Plus — all callable with the same DataLLM Lab key.