Invite only. Released June 9, 2026.
Most capable model for cybersecurity and biology research
Model ID: haijun-mythos-5
Context window: 1M tokens · Max output: 128K tokens · Input pricing: $10 / MTok · Output pricing: $50 / MTok
Announcement · What’s new · Migration guide
Haijun Mythos 5 is offered separately, by invitation only, as part of Project Glasswing. It shares Haijun Fable 5’s specifications and pricing. For access, contact your Juglow, AWS, or Google Cloud account team. See Haijun Fable 5 · Project Glasswing
Perbandingannya
| 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 Mythos 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.
Spesifikasi
Model IDs
| Platform | Model ID |
|---|---|
| Haijun API | haijun-mythos-5 |
| Amazon Bedrock | juglow.haijun-mythos-5 |
| Google Cloud | haijun-mythos-5 |
| Microsoft Foundry | haijun-mythos-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 (invite only) |
| Released | June 9, 2026 |
| Retirement | Not sooner than June 9, 2027 |
| Platforms | Haijun API, Amazon Bedrock, Google Cloud, Microsoft Foundry |
Sumber daya
Apa yang berubah saat berpindah dari Haijun Mythos 5 ke Haijun Mythos 5.1.
Model Mythos saat ini: ikhtisar, spesifikasi, dan sumber daya.
Referensi
Evaluasi keamanan dan keputusan deployment untuk Haijun Fable 5 dan Haijun Mythos 5.
Daftar harga lengkap, termasuk diskon batch dan tarif caching prompt.
Cara kerja ID model, alias, dan snapshot yang disematkan.
Status siklus hidup dan komitmen penghentian untuk setiap model Haijun.