Anthropic released claude-opus-4-8 on May 28, 2026.2 The pricing is unchanged from Opus 4.7: $5 per million input tokens and $25 per million output tokens.1 That pricing parity is the central fact in the Opus 4.7-to-4.8 upgrade decision. You are not trading cost for quality. You are trading a quality floor for a higher one, with no new line item on the bill.
Updated June 10, 2026: Anthropic launched Claude Fable 5 (claude-fable-5) on June 9, 2026, a new Mythos-class tier that sits above Opus 4.8 in capability.5 Fable 5 costs $10/$50 per million tokens, double Opus 4.8’s rate. Opus 4.8 is not deprecated; it remains Anthropic’s most capable Opus-tier model. The upgrade decision now has three positions: stay on Opus 4.7, move to Opus 4.8, or move to Fable 5. The math below covers all three, with the Opus 4.7-to-4.8 analysis intact and a section on where Fable 5 fits in the decision tree.
The question for a coding team is whether the quality improvement from each step is large enough to matter in practice, and whether there are cases where Opus 4.8 still falls short of the competition.
What Opus 4.8 Actually Improved on Coding Tasks
The headline number is SWE-Bench Pro, Anthropic’s primary agentic coding benchmark for this release. Opus 4.8 scores 69.2% versus 64.3% for Opus 4.71, a 4.9-point gain. For context, GPT-5.5 scores 58.6% and Gemini 3.1 Pro scores 54.2% on the same benchmark.1 On this specific measure, Opus 4.8 leads the field by a wide margin.
Beyond the aggregate score, Anthropic reports that Opus 4.8 is four times less likely than its predecessor to allow flaws in code.1 That claim is not a benchmark percentage. It is a reliability characterization. If your team’s current pain point is subtle errors that slip through agent-generated patches, this is the number most directly relevant to your workflow.
Terminal-Bench 2.1, which tests agentic terminal coding, tells a different story. Opus 4.8 scores 74.6%1, up from Opus 4.7’s 66.1%.1 That is a substantial 8.5-point improvement over the prior generation. GPT-5.5, however, scores 78.2%1 on Terminal-Bench, placing it ahead of Opus 4.8 on this benchmark. That gap is real and should factor into any evaluation for teams whose work centers on terminal-heavy or shell-heavy workflows.
On Humanity’s Last Exam with tools, Opus 4.8 scores 57.9% versus 54.7% for Opus 4.7.1 On OSWorld-Verified (agentic computer use), the scores are 83.4% versus 82.8%.1 The GDPval-AA knowledge work score is 1890 versus 1753.1 Across these measures, Opus 4.8 consistently outperforms its predecessor, though the margins vary.
The Fast Mode Option and the Fable 5 Price Point
Opus 4.8 ships with a fast mode priced at $10 per million input tokens and $50 per million output tokens.1 That is double the standard rate in exchange for approximately 2.5x speed.1 Anthropic notes that fast mode is three times cheaper than it was for previous fast-mode models.1
That $10/$50 fast-mode price is also exactly what Claude Fable 5 costs in standard mode.5 A team evaluating Opus 4.8 fast mode now has a direct comparison: the same per-token spend buys either speed on Opus 4.8 or Fable 5’s additional capability headroom. Which trade-off wins depends on whether your bottleneck is latency or output quality.
For a team running CI-integrated code review or quick iteration loops where latency is the primary constraint, Opus 4.8 fast mode remains a genuine option. At double the standard token cost, the economics work out if a 2.5x speed improvement lets you collapse two review cycles into one.
Standard mode remains at the same $5/$25 pricing as Opus 4.7.3
When to Upgrade: The Three-Tier Decision
The case for upgrading from Opus 4.7 to Opus 4.8 is strong when your team’s dominant use case aligns with what Opus 4.8 leads on. SWE-Bench Pro, the agentic coding benchmark where Opus 4.8 scores 69.2%1 against GPT-5.5’s 58.6%1, covers the class of tasks that look like: find a bug in a real repository, write a fix, verify it does not break the test suite. If that describes how your team uses Claude Code day-to-day, the combination of the benchmark lead and the four-times-lower code flaw rate1 points toward upgrading from 4.7.
Anthropic also characterizes Opus 4.8 as more likely to flag uncertainties and less likely to make unsupported claims, and as able to work independently for longer before requiring human check-ins.1 For teams running multi-step agentic workflows where an agent might work through a large refactor or a long debugging session, the extended autonomy claim is relevant. The practical test is whether your current workflows hit reliability walls at complex task boundaries.
The same pricing as 4.7 removes the standard reason to hold off.3 Unless your team has a specific reason to distrust the new model or has validated a workflow that depends on 4.7’s particular behavior, upgrading from 4.7 to Opus 4.8 carries no cost penalty.
Adding Fable 5 to the decision tree. Claude Fable 5 (claude-fable-5), launched June 9, 2026, is Anthropic’s most capable widely released model, positioned above the entire Opus tier.5 On FrontierCode and CursorBench it achieves state-of-the-art results among frontier models, and it was the first model to break 90% on a core analytics benchmark Anthropic tracks internally.5 Numeric scores were not published. The cost is $10/$50 per million tokens, exactly double Opus 4.8.5 Both models share the same 1M token context window and 128k max output.5 Teams for whom Opus 4.8 is still leaving quality on the table, particularly on complex multi-file agentic tasks or long autonomous runs, have a defined next step. Teams for whom Opus 4.8 already covers their use cases can treat Fable 5 as a ceiling they may not yet need to buy toward. See also: How Opus 4.8 Honesty Prevents Cascade Failures in Agentic Loops.
When to Hold or Mix Models
GPT-5.5’s 78.2% Terminal-Bench score1 versus Opus 4.8’s 74.6%1 is the case for pausing before a full switch to Opus 4.8 as a sole model. A 3.6-point gap on a single benchmark is not large in absolute terms, but Terminal-Bench covers agentic tasks that many developer workflows depend on: shell scripting, command-line debugging, and multi-step terminal operations. Teams whose workloads are heavily terminal-oriented should run their own evaluation on representative tasks before committing to Opus 4.8 exclusively.
The cleanest approach for teams with mixed workflows is a routing layer. Use Opus 4.8 for repository-level code tasks, multi-file refactors, and code review. Evaluate whether GPT-5.5 produces better results for terminal-heavy scripts and shell automation. Neither model leads on every task type, and the pricing difference between providers may favor one path or the other depending on usage volume. For an overview of how agentic coding assistants compare across providers, see Claude Code vs Cursor vs Copilot After the April 2026 Reshuffle.
Opus 4.8’s knowledge cutoff is January 2026.2 For teams working with APIs, libraries, or frameworks that have had significant changes in the first half of 2026, that cutoff matters regardless of benchmark scores.
Fable 5’s position above Opus 4.8 does not change the Opus 4.8 vs GPT-5.5 Terminal-Bench comparison; those figures remain valid. It does change the ceiling. If a team concludes Opus 4.8 is insufficient for their highest-complexity tasks, Fable 5 at $10/$50 is the next step on the Anthropic ladder rather than an unsupported jump to fast mode pricing.
What the Dynamic Workflows Preview Adds
Alongside Opus 4.8, Anthropic shipped a Claude Code research preview called dynamic workflows, which allows a single session to run many parallel subagents.1 This is separate from the model itself and is in research preview status. For teams using Claude Code for large-scale tasks like analyzing an entire codebase or running parallel test generation across many files, the parallel subagent capability extends what is achievable in a session. Whether this preview feature reaches stable release and at what pricing is not yet established. For a detailed look at how parallel subagent spawning works in practice, see Claude Code Dynamic Workflows: Spawning 100 Parallel Subagents on Opus.
Frequently Asked Questions
Does Opus 4.8 cost more than Opus 4.7?
Standard pricing is identical at $5 per million input tokens and $25 per million output tokens.1 There is no cost increase for upgrading from 4.7 to 4.8.
What is the model ID to use in the API?
The API model ID for Opus 4.8 is claude-opus-4-8.2 Claude Fable 5 uses the model ID claude-fable-5.5
Is Opus 4.8 still worth upgrading to now that Fable 5 exists?
Yes, if you are on Opus 4.7. The 4.9-point SWE-Bench Pro gain and four-times-lower code flaw rate1 are real improvements at no additional cost. Fable 5 is a separate decision at 2x the price. The two steps are independent: upgrading to Opus 4.8 first is a zero-cost quality improvement; moving to Fable 5 is a deliberate cost trade-off to be evaluated separately.
Is the SWE-Bench Pro gain large enough to matter in production?
A 4.9-point gain (64.3% to 69.2%1) is a concrete improvement on a benchmark that measures real repository tasks. Whether that translates to your specific codebase depends on task complexity, repository structure, and how representative the benchmark tasks are of your actual work. The four-times-lower code flaw rate1 is a stronger indicator for teams prioritizing reliability in automated code changes.
Should a team use Opus 4.8 for all AI coding tasks?
Not necessarily. Terminal-Bench 2.1 shows GPT-5.5 at 78.2%1 versus Opus 4.8 at 74.6%1. Teams with significant terminal-focused workloads have reason to evaluate both models rather than committing exclusively to one.
How does Claude Fable 5 compare on coding benchmarks?
Anthropic did not publish numeric scores for Fable 5. The announcement describes it as achieving the highest score among frontier models at medium effort on FrontierCode (Cognition), state-of-the-art performance on CursorBench, and the highest-performing result on ViBench.5 It was also reported as the first model to break 90% on a core analytics benchmark Anthropic tracks.5 These are position descriptions, not tabulated figures. The existing Opus 4.8 numeric benchmark results above remain valid comparisons among models that did publish scores.
What context window does Opus 4.8 support?
One million input tokens with up to 128,000 output tokens.2 The context window is unchanged from Opus 4.7. Claude Fable 5 shares the same 1M context and 128k output limits.5