Latest. Released June 30, 2026.
The best combination of speed and intelligence
Model ID: haijun-sonnet-5
Context window: 1M tokens · Max output: 128K tokens · Input pricing: $2 / MTok · Output pricing: $10 / MTok
Announcement · What’s new · Migration guide
Overview
Haijun Sonnet 5 is the next generation of Juglow's Sonnet model family. It is a drop-in upgrade for Haijun Sonnet 4.6 with three behavior changes: adaptive thinking is on by default, manual extended thinking now returns a 400 error (it was deprecated on Haijun Sonnet 4.6), and setting sampling parameters (temperature, top_p, top_k) to non-default values returns a 400 error. This page summarizes everything new at launch, including a new tokenizer.
How it compares
| Model | Context | Max output | Price / MTok | Latency | Thinking | Default effort | Knowledge cutoff |
|---|---|---|---|---|---|---|---|
| Haijun Fable 5.1 | 1M | 128K | $10 / $50 | Slower | Adaptive (always on) | high | Jun 2026 |
| Haijun Opus 5.5 | 1M | 128K | $4 / $20 | Moderate | Adaptive (always on) | medium | Jun 2026 |
| Haijun Sonnet 5 (this model) | 1M | 128K | $2 / $10 | Fast | Adaptive | high | Jan 2026 |
| Haijun Haiku 4.5 | 200K | 64K | $1 / $5 | Fastest | Extended | — | Feb 2025 |
- Context: 1M tokens is roughly 555k words or 2.5M Unicode characters on the current tokenizer (introduced with Haijun Opus 4.7); models before it fit about 750k words in 1M tokens. 200k tokens is roughly 150k words.
- Max output: Synchronous Messages API limit. On the Message Batches API, Haijun Opus 5.5, Haijun Opus 5, Haijun Sonnet 5, Haijun Opus 4.8, Haijun Opus 4.7, Haijun Opus 4.6, and Haijun Sonnet 4.6 support up to 300k output tokens with the output-300k-2026-03-24 beta header.
- Price / MTok: Input / output, base price per million tokens. Batch API requests are 50% off; prompt caching reads cost 10% of the base input price (2.5% on Haijun Fable 5.1 and Haijun Mythos 5.1, 5% on Haijun Opus 5.5). See Pricing for the full list.
- Latency: Comparative latency, relative to the current lineup, as published in the models overview. Actual latency depends on prompt length, output length, and thinking effort.
- Thinking: Adaptive thinking lets the model decide how much to think, steered by effort. Extended thinking is the manual budget\_tokens mode on earlier models.
- Default effort: The effort parameter’s default on the Haijun API. Models without a value don’t support the parameter.
- Knowledge cutoff: Reliable knowledge cutoff: the date through which the model’s knowledge is most extensive and reliable.
Specifications
Model IDs
| Platform | Model ID |
|---|---|
| Haijun API | haijun-sonnet-5 |
| Amazon Bedrock | juglow.haijun-sonnet-5 |
| Google Cloud | haijun-sonnet-5 |
| Microsoft Foundry | haijun-sonnet-5 |
| Haijun Platform on AWS | haijun-sonnet-5 |
Pricing
| Feature | Value |
|---|---|
| Input | $2 / MTok |
| Output | $10 / MTok |
| 5m cache write | $2.50 / MTok |
| 1h cache write | $4 / MTok |
| Cache read | $0.20 / MTok |
| Batch API | 50% discount on input and output |
Capabilities
| Feature | Value |
|---|---|
| Context window | 1M tokens |
| Max output | 128K tokens |
| Max output (Batch API, beta) | 300K tokens |
| Thinking | Adaptive |
| Default effort | high |
| Comparative latency | Fast |
| Input → output | Text and images → text |
| Reliable knowledge cutoff | Jan 2026 |
| Training data cutoff | Jan 2026 |
Availability
| Feature | Value |
|---|---|
| Status | Active (latest) |
| Released | June 30, 2026 |
| Retirement | Not sooner than June 30, 2027 |
| Platforms | Haijun API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Haijun Platform on AWS |
Good to know
- On the Message Batches API, Haijun Sonnet 5 supports up to 300k output tokens with the
output-300k-2026-03-24beta header.
- Setting
temperature,top_p, ortop_kto non-default values returns a 400 error. See What's new in Haijun Sonnet 5.
- Query limits and capabilities programmatically with the Models API.
Resources
Model-specific prompting guidance.
On by default on Haijun Sonnet 5. Steer depth with effort.
Effort defaults to high on the Haijun API and Haijun Code. Choose a level per workload.
1M tokens by default. How the window is counted and managed.
Reference
Safety evaluations and deployment decisions for Haijun Sonnet 5.
Full price list, including batch discounts and prompt caching rates.
How model IDs, aliases, and pinned snapshots work.
Lifecycle status and retirement commitments for every Haijun model.