morph
Morph: Morph V3 Large (batch)
morph/morph-v3-large:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter’s catalog describes morph/morph-v3-large:batch as the Morph V3 Large apply model for complex code edits, accepting text input and producing text output within a stated long context window. It reports high throughput and high accuracy for precise transformations, but the supplied evidence does not identify independent measurements. The catalog also specifies a required prompt pattern that separates editing instructions from the code. An independent model card was not available in this source pack.[1]
Strengths
Limitations
- Evidence is catalog-only; an independent model card was unavailable, so throughput, accuracy, and edit quality need validation on the intended workload.[1]
- The supplied record contains no benchmark entries, knowledge cutoff, or reasoning designation; those details are unknown rather than established negatives.[1]
- It requires a specific instruction-and-code prompt layout, so integrations may need dedicated formatting.[1]
Where to use it
- Consider for complex code-edit application after testing on representative repositories and prompts.[1]
- Candidate for text-to-text transformation pipelines that can generate the required prompt structure.[1]
- May be evaluated for structured code-edit responses where declared structured-output support is important.[1]
Sources
- [1] OpenRouter catalog · Morph: Morph V3 Large (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
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>...
Specifications
- Model ID
- morph/morph-v3-large:batch
- Canonical ID
- morph/morph-v3-large
- Creator
- morph
- Added to OpenRouter
- 07.07.2025
- Context length
- 262,144
- Modality
- text->text
- Input modalities
- text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.450 / out $0.950
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs |
| Writing | No measurement | output: text |
| Reasoning | No measurement | — |
| Document analysis | No measurement | — |
| Vision | No measurement | — |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Morphfp8 | 262,144 | $0.450 | $0.950 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.