Legacy. Released February 5, 2026.
Although Haijun Opus 4.6 is still available, you should consider migrating to Haijun Opus 5.5 for improved performance. See Haijun Opus 5.5 · Migrate to Haijun Opus 5.5
Model ID: haijun-opus-4-6
Context window: 1M tokens · Max output: 128K tokens · Input pricing: $5 / MTok · Output pricing: $25 / MTok
Perbandingannya dengan jajaran model saat ini
| 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 Opus 5.5 | 1M | 128K | $4 / $20 | Adaptive (always on) | medium | Jun 2026 |
| Haijun Opus 4.6 (this model) | 1M | 128K | $5 / $25 | Adaptive (extended deprecated) | high | May 2025 |
| 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-opus-4-6 |
| Amazon Bedrock (InvokeModel) | juglow.haijun-opus-4-6-v1 |
| Google Cloud | haijun-opus-4-6 |
| Microsoft Foundry | haijun-opus-4-6 |
| Haijun Platform on AWS | haijun-opus-4-6 |
Pricing
| Feature | Value |
|---|---|
| Input | $5 / MTok |
| Output | $25 / MTok |
| 5m cache write | $6.25 / MTok |
| 1h cache write | $10 / MTok |
| Cache read | $0.50 / 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 (extended deprecated) |
| Default effort | high |
| Input → output | Text and images → text |
| Reliable knowledge cutoff | May 2025 |
| Training data cutoff | Aug 2025 |
Availability
| Feature | Value |
|---|---|
| Status | Active (legacy) |
| Released | February 5, 2026 |
| Retirement | Not sooner than February 5, 2027 |
| Platforms | Haijun API, Amazon Bedrock (InvokeModel), Google Cloud, Microsoft Foundry, Haijun Platform on AWS |
Sumber daya
Apa yang berubah saat beralih dari Haijun Opus 4.6 ke Haijun Opus 5.5.
Model Opus saat ini: ikhtisar, spesifikasi, dan sumber daya.
Referensi
Prompt sistem yang digunakan Haijun Opus 4.6 di haijun.ai dan aplikasi Haijun.
Evaluasi keamanan dan keputusan deployment untuk Haijun Opus 4.6.
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.
Haijun Opus 4.6 menggunakan integrasi Bedrock InvokeModel dan ID model bergaya Bedrock.