Current lineup (updated July 6, 2026): Claude Fable 5 is the top tier above Opus, with Claude Opus 4.8 the current Opus, Claude Sonnet 5 (released June 30, 2026), and Claude Haiku 4.5. Opus 4.7 is now a legacy model. Full lineup: Claude Fable 5 guide. Claude Opus 4.7 referenced in this article has been superseded. See current model tracker →
Anthropic released Claude Opus 4.7 on April 16, 2026, alongside an update to Claude Haiku 4.5. The release is headlined by a 3× improvement in vision resolution, but the more operationally significant additions are task budgets and the new xhigh effort level — both of which change how developers can dial Claude’s reasoning intensity for compute-sensitive workflows.
Vision Resolution: What 3× Actually Means
Vision resolution — what 3× actually means.
Claude Opus 4.7 processes images at three times the resolution of its predecessor. In practice, this means documents with dense text, screenshots of complex interfaces, detailed charts and diagrams, and high-resolution photography are now meaningfully more legible to the model. Tasks that previously required cropping or pre-processing images to help Claude read fine details should now work with the original image.
For enterprise use cases — contract review from scanned PDFs, financial statement analysis from images, medical imaging workflows, engineering diagram interpretation — the resolution improvement is not incremental. It crosses a threshold where image-based document processing becomes reliably useful rather than occasionally accurate.
Task Budgets
Task budgets.
Task budgets give developers a mechanism to cap how much compute Claude spends on a given task before returning a response. This is the missing lever that has made Claude’s extended thinking mode difficult to use predictably in production. Without a budget ceiling, extended thinking tasks could run arbitrarily long and cost arbitrarily much. With task budgets, you can set a ceiling and get a best-effort response within that constraint rather than an open-ended spend.
The practical implication is that extended thinking becomes viable in latency-sensitive or cost-sensitive production contexts that previously had to avoid it entirely. A customer-facing workflow that needs a thoughtful answer but can’t wait indefinitely can now specify a budget and get a response calibrated to that constraint.
The xhigh Effort Level
The xhigh effort level.
Alongside the existing effort levels, Opus 4.7 introduces xhigh — an above-maximum reasoning intensity setting intended for tasks where accuracy justifies extended compute time regardless of cost. Research tasks, complex multi-step reasoning chains, high-stakes analysis where a wrong answer is costly — these are the intended use cases.
xhigh pairs naturally with task budgets: use xhigh to get the most thorough reasoning Claude can produce, and use a task budget to define the ceiling on how long it runs. Together they give developers precision control over the quality/cost/latency trade-off that was previously binary (extended thinking on or off).
Pricing: Unchanged from 4.6
Opus 4.7 maintains the same pricing as Claude Opus 4.7: $5 per million input tokens and $25 per million output tokens. For teams currently on Opus 4.6, this is an unambiguous upgrade — better vision, task budgets, and xhigh effort at the same cost. The Haiku 4.5 update released alongside it carries the same pricing-unchanged pattern.
Deprecation note: Claude Haiku 3 was retired on April 19. Teams still on Haiku 3 should have already migrated — if not, that’s an urgent action item.
Direct Answer (August 2026): Claude features a 200,000-token context window (~150,000 words) across all models and tiers, capable of ingesting entire codebases, financial filings, or 500-page manuals in a single prompt with 99.5%+ needle-in-a-haystack recall.
Looking for quick answers? The FAQ version covers every common question directly.
Claude’s context window is one of those specs that sounds simple until you actually need to use it. “1 million tokens” means almost nothing without a frame of reference. This is the guide we wish existed when we started building on Claude — written from our own experience running it in production, with numbers pulled directly from Anthropic’s official documentation.
Quick Definition
The context window is Claude’s working memory for a conversation. It holds everything Claude can see and reason about at once: your messages, Claude’s responses, any documents you’ve shared, and system prompts. When the window fills up, earlier content drops out.
Current Context Window Sizes by Model (June 2026)
Current context window sizes by model.
These numbers come directly from Anthropic’s official models page, fetched May 9, 2026. Model strings are exact API identifiers:
Model
API String
Context Window
Max Output
Claude Fable 5
claude-fable-5
1,000,000 tokens
128,000 tokens
Claude Opus 4.8
claude-opus-4-8
1,000,000 tokens
128,000 tokens
Claude Sonnet 5
claude-sonnet-4-6
1,000,000 tokens
64,000 tokens
Claude Haiku 4.5
claude-haiku-4-5-20251001
200,000 tokens
64,000 tokens
Fable 5, Opus 4.8, and Sonnet 5 all have the full 1M token context window. Haiku 4.5 is 200K. The key difference between Opus 4.8 and Sonnet 5 in this table is the max output — Opus 4.8 can write up to 128K tokens in a single response, Sonnet 5 caps at 64K.
What Does 1 Million Tokens Actually Hold?
Token counts are an abstraction. Here’s what 1 million tokens translates to in practical terms:
About 750,000 words of English text — roughly 10 full-length novels, or 1,500 average blog posts
A full mid-size codebase — a 50,000-line Python project with comments fits comfortably
Hours of meeting transcripts — a full workday of recorded calls, transcribed, fits in one context window
Multiple large documents simultaneously — 10 research PDFs at 30 pages each, all in the same conversation
Long conversation histories — hundreds of back-and-forth exchanges before anything starts dropping off
We’ve loaded entire Notion exports, full project histories, and multi-document research packs into a single Claude session. At 1M tokens, you’re unlikely to hit the ceiling in a normal working session. You hit it when you’re doing things like: loading your entire codebase plus documentation plus conversation history and then asking Claude to do a full architectural review.
Context Window vs. Memory: What’s the Difference?
Context window vs memory — what’s the difference?
This is where a lot of people get confused. The context window and memory are not the same thing:
Context window: What Claude can see right now, in this session. Once a session ends, it’s gone.
Memory (in claude.ai): A separate system that extracts and stores key information from past sessions. It surfaces relevant facts into future conversations as a snippet in the context.
Managed Agents memory stores: A developer-layer construct where agents maintain and update knowledge bases across sessions — distinct from both the context window and the consumer memory feature.
The 1M token context window is your working memory for one session. It doesn’t persist. Memory systems are what carry information across sessions — but they work by injecting a summary into the context window of the new session, not by giving Claude access to the full history.
Does a Bigger Context Window Mean Better Performance?
Mostly yes, with one important nuance. More context means Claude has more information to reason about, which generally produces better outputs for tasks that benefit from full context — code reviews, document synthesis, long-form writing, multi-document comparison.
The nuance: performance can degrade on tasks involving specific information buried deep in a very long context. This is sometimes called the “lost in the middle” problem — models tend to pay more attention to the beginning and end of a long context than the middle. Anthropic has worked on this with Claude’s architecture, and it performs well on long-context tasks, but it’s worth structuring important information at natural reference points rather than burying it in the middle of a 500-page document.
How We Actually Use the 1M Token Window
How we actually use the 1M token window.
We run Claude in production for content operations, site management, and agentic coding workflows. Here’s where the 1M context window makes a concrete difference in our work:
Full site audits: Loading every post from a WordPress site (200+ posts worth of content) into one session for comprehensive SEO analysis — without having to chunk and re-prompt
Cross-session context: Pasting in long Notion briefings, prior session transcripts, and the current task in one go. The window is large enough that we don’t have to decide what to leave out.
Codebase-wide reasoning: In Claude Code, having the full project context means Claude can make changes that account for how files interact rather than reasoning only about the current file
Multi-document synthesis: Research projects where we load 10-15 source documents and ask Claude to synthesize across them — something that was impossible at 100K context windows
The practical shift from 200K to 1M tokens wasn’t just “more room.” It changed what we could ask Claude to do in a single session.
Context Window on the API: Batch Output Extension
For API users: on the Message Batches API, Fable 5, Opus 4.8, and Sonnet 5 support up to 300K output tokens using the output-300k-2026-03-24 beta header. This is relevant for batch generation tasks where you need very long outputs — documentation generation, large codebases, book-length content.
Frequently Asked Questions
What is Claude’s context window in 2026?
Claude Fable 5, Claude Opus 4.8, and Claude Sonnet 5 all have 1,000,000 token (1M token) context windows as of June 2026. Claude Haiku 4.5 has a 200,000 token context window. These are the current generally available models.
How many pages can Claude read at once?
At 1M tokens, Claude can hold roughly 750,000 words of English text — equivalent to approximately 3,000 average pages. In practice, a typical 20-page PDF is roughly 10,000-15,000 tokens, so you could load 60-100 such documents in a single session before approaching the limit.
Does the context window reset between messages?
No — the context window accumulates across an entire conversation session. Every message you send and every response Claude gives adds to the total. The window doesn’t reset between individual messages; it resets when you start a new conversation.
What happens when Claude hits the context window limit?
When a conversation reaches the context window limit, earlier messages begin to drop out of the active context. Claude can no longer reference information from those earlier messages — it effectively forgets that part of the conversation. In the claude.ai interface, you’ll see a notification when you’re approaching the limit.
Is the 1M context window available on the free plan?
The model available to free plan users has access to the 1M context window. However, free plan usage limits mean long-context sessions hit rate limits faster than paid plans. The window is technically available, but sustained heavy use of it is more practical on paid tiers.
What’s the difference between Claude Opus 4.8 and Sonnet 5 context windows?
Both have the same 1M token input context window. The difference is max output: Opus 4.8 can generate up to 128,000 tokens in a single response; Sonnet 5 caps at 64,000 tokens. For most tasks this distinction doesn’t matter, but for very long document generation or large code outputs, Opus 4.8 has the higher output ceiling.
💼 Deploying Claude or AI Infrastructure in Your Business?
Last verified: 8 September 2026. Dollars and current names live on Claude pricing and the model tracker. This page is the pick-by-job desk, not a second rate card.
Direct Answer (8 September 2026): Default production: Sonnet 5 ($2 / $10). Hard agent / coding: Opus 5 ($5 / $25). Only if the job is worth it: Fable 5.1 ($10 / $50). Volume / smoke test: Haiku 4.5 ($1 / $5). Sonnet 4.6 at $3 / $15 and Opus 4.8 at $5 / $25 remain on the API list — do not start new work on them.
Seat
Current name
API $ in / out
Context
Use
Top public
Fable 5.1
$10 / $50
1M
Hardest coding and knowledge work
Opus
Opus 5
$5 / $25
1M
Anthropic’s recommended API starting point for most workloads