Choose a model - Writer AI Studio

Model comparison

The following table compares the capabilities, context windows, and pricing of the Palmyra X5 and X4 models.

All Palmyra models are available in No-code, Agent Builder, and API. To analyze images, use vision capabilities with Palmyra X5.

Model details

Palmyra X5

Palmyra X5 is Writer’s newest and most advanced model for building and scaling AI agents, featuring a 1 million token context window, adaptive reasoning, and industry-leading speed and cost efficiency.

Pricing:

• Input: $0.60 per 1M tokens
• Output: $6.00 per 1M tokens

Content window: 1M

Palmyra X5’s 1M token context window further streamlines enterprise workflows and unlocks complex, multi-step use cases that weren’t possible before.

Multi-step agentic workflows

• Support documentation: Classify requests, assess urgency, assign a human review, stage updates in a CMS, and publish after approval.
• Fund reporting: Streamline the analysis and preparation of detailed reports on the performance and status of investment funds, using reporting and research data pulled in from third-party systems.
• Content lifecycle management: Flag content that could be outdated, generate suggested revisions, and share them for human review.

Large data requirements

• Customer feedback analysis: Analyze large volumes of customer feedback to identify common themes, summarize sentiments, and generate actionable insights.
• Research and development: Process and summarize multiple technical reports, research papers, and experimental data, accelerating innovation and product development.
• Financial reporting: Process and summarize annual reports, SEC filings, and market analysis reports together at once to extract financial data, identify trends, and generate executive summaries.
• Legal document analysis: Analyze lengthy legal documents, including contracts, patents, and compliance reports, to identify key clauses, flag potential risks, and ensure regulatory compliance.
• Medical records analysis: Analyze and summarize large files of medical records containing structured and unstructured data, including patient records, clinical trial reports, audit reports, and more.

Palmyra X5 demonstrates robust performance across a suite of industry-standard benchmarks, showcasing its capabilities in reasoning, retrieval, and domain-specific tasks.

Benchmarking

• BBH (Big-Bench Hard): Palmyra X5 achieves a competitive score of 70.99%.
• GPQA (Graduate-Level Google-Proof Q&A): X5’s score of 47.20% indicates strong performance in scientific reasoning tasks.
• MMLU_PRO: Palmyra X5 scores 65.02%, demonstrating its suitability for enterprise applications in regulated sectors.
• MATH_HARD: X5’s score of 71.57% showcases its proficiency in handling complex analytical tasks.

Palmyra X4

palmyra-x4 is an advanced language model that excels in processing and understanding complex tasks. It is ideal for workflow automation, coding tasks, and data analysis.

Pricing:

• Input: $2.50 per 1M tokens
• Output: $10.00 per 1M tokens

Content window: 128k

• Agents & actions: Palmyra X4 acts as an advanced AI agent, capable of executing tasks beyond simple text generation by interacting with external systems.
• Retrieval-augmented generation (RAG): Equipped with RAG, Palmyra X4 can retrieve and incorporate relevant information from vast data sources.
• Code generation: The model supports advanced code generation, enabling it to automate scripting.
• Tool calling: Palmyra X4 is built to handle precise API interactions.

Palmyra X4 consistently ranks at the top in structured output, API tool calling, and accuracy for complex multi-step workflows.

Benchmarking

• Top accuracy (ACC): Palmyra X4 achieves 78.76% accuracy in tool call identification and execution.
• Structured call planning (AST): Palmyra X4 scores 87.93%.
• Execution performance (Exec): With an 88.27% score in executing tool calls.
• Global benchmarks: Palmyra X4 ranks in the world’s top 10 on HELM Lite (86.1%) and HELM MMLU (81.3%).

Using models with the Writer API

To select the Palmyra model you want to use for a chat completion, specify the model ID in the model parameter of the request.

Example in cURL

curl --location 'https://api.writer.com/v1/chat' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $WRITER_API_KEY" \
--data '{
  "model": "palmyra-x5",
  "messages": [\
    {\
      "role": "user",\
      "content": "Summarize GDPR compliance requirements for a cloud-based data storage provider"\
    }\
  ]
}'

Example in Python

from writerai import Writer

client = Writer()

chat_completion = client.chat.completions.create(
  model="palmyra-x5",
  messages=[\
    {\
      "role": "user",\
      "content": "Summarize GDPR compliance requirements for a cloud-based data storage provider"\
    }\
  ]
)

print(chat_completion.choices[0].message.content)

Example in JavaScript

import { Writer } from 'writer-sdk';

const client = new Writer();

const chat_completion = await client.chat.completions.create({
  model: 'palmyra-x5',
  messages: [\
    {\
      "role": "user",\
      "content": "Summarize GDPR compliance requirements for a cloud-based data storage provider"\
    }\
  ]
});

console.log(chat_completion.choices[0].message.content);

To select the Palmyra model you want to use for text generation, specify the model ID in the model parameter of the request.

Example in cURL

curl --location 'https://api.writer.com/v1/completions' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $WRITER_API_KEY" \
--data '{
  "model": "palmyra-x5",
  "prompt": "Summarize GDPR compliance requirements for a cloud-based data storage provider"
}'

Example in Python

from writerai import Writer

client = Writer()

text_generation = client.completions.create(
  model="palmyra-x5",
  prompt="Summarize GDPR compliance requirements for a cloud-based data storage provider"
)

print(text_generation.choices[0].text)

Example in JavaScript

import { Writer } from 'writer-sdk';

const client = new Writer();

const text_generation = await client.completions.create({
  model: 'palmyra-x5',
  prompt: 'Summarize GDPR compliance requirements for a cloud-based data storage provider'
});

console.log(text_generation.choices[0].text);

Deprecation policy

Timeline for deprecation

• We’ll announce the deprecation of a model at least three months in advance.
• We’ll continue to support deprecated models for a period of time after they’re deprecated.
• We’ll eventually stop supporting deprecated models.

Deprecated models

Migration path

• We’ll provide customers with a migration path to the new model, including detailed documentation and support to help them migrate their applications.
• We’ll also offer training and consulting services to help customers transition.