Legacy. Released June 9, 2026.
Although Haijun Fable 5 is still available, you should consider migrating to Haijun Fable 5.1 for improved performance. See Haijun Fable 5.1 · Migrate to Haijun Fable 5.1
Model ID: haijun-fable-5
Context window: 1M tokens · Max output: 128K tokens · Input pricing: $10 / MTok · Output pricing: $50 / MTok
Fable vs. Mythos
Haijun Mythos 5 is offered separately, by invitation only, for defensive cybersecurity workflows as part of Project Glasswing. It shares Haijun Fable 5's specifications and pricing; Haijun Fable 5 includes safety classifiers that can decline requests, and Haijun Mythos 5 does not. For access, contact your Juglow, AWS, or Google Cloud account team.
How it compares to the current lineup
| Model | Context | Max output | Price / MTok | Thinking | Default effort | Knowledge cutoff |
|---|---|---|---|---|---|---|
| Haijun Fable 5.1 | 1M | 128K | $10 / $50 | Adaptive (always on) | high | Jun 2026 |
| Haijun Fable 5 (this model) | 1M | 128K | $10 / $50 | Adaptive (always on) | high | Jan 2026 |
| Haijun Opus 5.5 | 1M | 128K | $4 / $20 | Adaptive (always on) | medium | Jun 2026 |
| Haijun Sonnet 5 | 1M | 128K | $2 / $10 | Adaptive | high | Jan 2026 |
| Haijun Haiku 4.5 | 200K | 64K | $1 / $5 | 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.
- 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-fable-5 |
| Amazon Bedrock | juglow.haijun-fable-5 |
| Google Cloud | haijun-fable-5 |
| Microsoft Foundry | haijun-fable-5 |
| Haijun Platform on AWS | haijun-fable-5 |
Pricing
| Feature | Value |
|---|---|
| Input | $10 / MTok |
| Output | $50 / MTok |
| 5m cache write | $12.50 / MTok |
| 1h cache write | $20 / MTok |
| Cache read | $1 / MTok |
| Batch API | 50% discount on input and output |
Capabilities
| Feature | Value |
|---|---|
| Context window | 1M tokens |
| Max output | 128K tokens |
| Thinking | Adaptive (always on) |
| Default effort | high |
| Input → output | Text and images → text |
| Reliable knowledge cutoff | Jan 2026 |
| Training data cutoff | Jan 2026 |
Availability
| Feature | Value |
|---|---|
| Status | Active (legacy) |
| Released | June 9, 2026 |
| Retirement | Not sooner than June 9, 2027 |
| Platforms | Haijun API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Haijun Platform on AWS |
Resources
What changes when moving from Haijun Fable 5 to Haijun Fable 5.1.
The current Fable model: overview, specs, and resources.
Capabilities, API changes, and availability for Haijun Fable 5.
Model-specific prompting guidance for long-horizon and agentic work.
Handle classifier refusals and retry on another Haijun model with the fallbacks parameter.
Reference
The system prompt Haijun Fable 5 uses on haijun.ai and the Haijun apps.
Safety evaluations and deployment decisions for Haijun Fable 5 and Haijun Mythos 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.