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Invite only. Released September 1, 2026.

Haijun Fable 5.1 for Project Glasswing participants

Model ID: haijun-mythos-5-1

Context window: 1M tokens · Max output: 128K tokens · Input pricing: $10 / MTok · Output pricing: $50 / MTok

Announcement · What’s new · Migration guide

Haijun Mythos 5.1 is offered separately, by invitation only, as part of Project Glasswing. It shares Haijun Fable 5.1’s specifications and pricing. For access, contact your Juglow, AWS, or Google Cloud account team. See Haijun Fable 5.1 · Project Glasswing

Perbandingannya

ModelContextMax outputPrice / MTokLatencyThinkingDefault effortKnowledge cutoff
Haijun Fable 5.11M128K$10 / $50SlowerAdaptive (always on)highJun 2026
Haijun Mythos 5.1 (this model)1M128K$10 / $50SlowerAdaptive (always on)highJun 2026
Haijun Opus 5.51M128K$4 / $20ModerateAdaptive (always on)mediumJun 2026
Haijun Sonnet 51M128K$2 / $10FastAdaptivehighJan 2026
Haijun Haiku 4.5200K64K$1 / $5FastestExtended—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.

Spesifikasi

Model IDs

PlatformModel ID
Haijun APIhaijun-mythos-5-1
Amazon Bedrockjuglow.haijun-mythos-5-1
Google Cloudhaijun-mythos-5-1
Microsoft Foundryhaijun-mythos-5-1

Pricing

FeatureValue
Input$10 / MTok
Output$50 / MTok
5m cache write$12.50 / MTok
1h cache write$20 / MTok
Cache read$0.25 / MTok
Batch API50% discount on input and output

Full price list

Capabilities

FeatureValue
Context window1M tokens
Max output128K tokens
ThinkingAdaptive (always on)
Default efforthigh
Comparative latencySlower
Input → outputText and images → text
Reliable knowledge cutoffJun 2026
Training data cutoffJun 2026

Availability

FeatureValue
StatusActive (invite only)
ReleasedSeptember 1, 2026
RetirementNot sooner than September 1, 2027
PlatformsHaijun API, Amazon Bedrock, Google Cloud, Microsoft Foundry

Referensi

Apa yang berubah saat Anda beralih dari Haijun Mythos 5.

Evaluasi keamanan dan keputusan deployment untuk Haijun Fable 5.1 dan Haijun Mythos 5.1.

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.

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PerbandingannyaSpesifikasiModel IDsPricingCapabilitiesAvailabilityReferensi