LANGUAGE MODEL Anthropic Last updated:

Claude Instant

Claude Instant is an API model from Anthropic. It’s positioned for general text tasks—work that benefits from iteration, not just one-shot answers.

Context
100K
Up to 100,000 tokens

Core Capabilities

Long Documents
Handles entire codebases, books, and multi-doc RAG.

Context Window

100k tokens
≈ 77 pages
4k Chat 聊天
32k Long docs 长文档
128k This model 本模型
400k Multi-doc 多文档
1M Codebase 整个代码库
10M

Availability

API
Available
Product / App
Not available
Open Source
Not released
Enterprise
Contact sales

Pricing Model

Pay per token
Input and output billed separately.
Pay-per-token

Capability / Performance

Where this model sits relative to the middle 60% of models in the tree. All scores are 0–10 (higher is better).

Lower 20% Upper 80% This model
Reasoning
AA Intelligence Index · scaled to 10
1.7
5.6
1.1
Coding
AA Coding Index · scaled to 10
1.8
4.3
1.1
Context / memory
Context window size · log-scaled
6.0
9.0
5.7
Lower 20% 20th percentile — 20% of models score below this This model Where the current model lands Upper 80% 80th percentile — only 20% of models score above this Percentile boundaries are computed across every model in the tree that reports the underlying benchmark for each capability.

What it feels like

  • Earlier fast-tier Claude — superseded by Haiku family.
  • Three tiers (Opus / Sonnet / Haiku) — first time the same family covered flagship-quality and ultra-fast in one release
  • Opus Needle-in-Haystack: 99.4% recall average, 98.3% even at 200K tokens — long-context that genuinely works
  • Opus 90.5% one-shot, 89.2% zero-shot — set new state-of-the-art on multiple expert benchmarks

Best use cases

  • Long-document analysis (200K context with reliable retrieval)
  • Vision + text tasks where Opus / Sonnet outperform GPT-4V
  • Deployments needing a tier-aware family (Haiku triage → Sonnet workflow → Opus hard cases)

Tools to try

Not ideal for

  • Bleeding-edge reasoning by 2025 — superseded by Claude 3.5 / 3.7 / 4 family
  • Self-hosted / open-weights deployments