# Claude Haiku 4.5 vs Claude Fable 5 (2026): side-by-side comparison Source: [GLAD-AI-TOR](https://glad-ia-tor.com) · Full page: https://glad-ia-tor.com/vs/claude-haiku-4-5-vs-claude-fable-5 Arena: llm-models · Crowd scores are live visitor verdicts (one per person per tool, never paid, Bayesian-smoothed). ## At a glance | | Claude Haiku 4.5 | Claude Fable 5 | |---|---|---| | Price | $5/1M out | $50/1M out | | Crowd score | 67% (2 votes) | 63% (4 votes) | | provider | Anthropic | Anthropic | | contextWindow | 200K tokens | 1M tokens | | priceIn | $1/1M in | $10/1M in | | priceOut | $5/1M out | $50/1M out | | modalities | text, vision (input); text output | text, vision | | openWeights | no | no | | reasoning (1-5) | 3 | 5 | | coding (1-5) | 3.5 | 5 | | writing (1-5) | 3 | 4.5 | | speed (1-5) | 4.5 | 2 | | valueForMoney (1-5) | 4 | 3 | ### Claude Haiku 4.5 > Anthropic's fastest model: about 90% of Sonnet 4.5's coding skill at $1/$5 per 1M tokens, 200K context. Strengths: - 73.3% on SWE-bench Verified, about 90% of Sonnet 4.5's agentic coding at one third of the price - Fast: more than 2x Sonnet 4 speed per Anthropic, with launch customers reporting 4-5x faster than Sonnet 4.5; ~92-110 output tok/s measured by Artificial Analysis - Devs report precise, localized code edits that avoid touching irrelevant code, better than GPT-5 mini class in early testing - Supports both vision input and extended thinking, rare at this price tier at launch Weaknesses: - $5/1M output is pricey for a small model: Gemini Flash and GPT mini tiers undercut it several-fold on output-heavy tasks - 200K context (vs 1M for Sonnet 5/Opus siblings) and 64K max output limit large-codebase and long-output work - Mediocre cross-domain reasoning: users report weak results on GPQA, MedQA, MMMU style knowledge tasks Verdict: Pick Haiku 4.5 if you are on the Anthropic stack and need near-Sonnet coding quality at low latency and a third of the price: it is a massive step up from Haiku 3.5 and excels as the worker model in multi-agent pipelines. It remains Anthropic's current small model as of July 2026, so it is the default cheap tier for Claude-based products. Avoid it for deep cross-domain reasoning, very large codebases (200K context cap), or pure cost-per-token shopping, where Gemini Flash and GPT mini tiers are now cheaper, and step up to Sonnet 5 when quality matters more than speed. Full review: https://glad-ia-tor.com/tool/claude-haiku-4-5 · Markdown: https://glad-ia-tor.com/tool/claude-haiku-4-5.md ### Claude Fable 5 > Anthropic's June 2026 Mythos-class flagship: 80.3% on SWE-bench Pro, 11 points clear of every other frontier model Strengths: - 80.3% on SWE-bench Pro vs 69.2% for Opus 4.8, 58.6% for GPT-5.5 and 54.2% for Gemini 3.1 Pro, roughly 11 points ahead of the next frontier model - 95.0% on SWE-bench Verified (Opus 4.8: 88.6%, GPT-5.5: 82.6%) and 29.3% on Cognition's FrontierCode Diamond split, more than double Opus 4.8's 13.4% - Long-horizon autonomy is the real story: Stripe reported a 50-million-line Ruby codebase migration done in one day instead of 2+ months, and Cursor's CEO calls it state of the art on CursorBench - Field reports match the benchmarks: HN engineers describe it working 'like an actual engineer' (CRDTs with minimal hand-holding, writing its own fuzzers, one 46x allocation reduction), Simon Willison measured 'several days' worth of work' in a single session Weaknesses: - Double the price of Opus 4.8 ($10/$50 vs $5/$25) and slow: single requests on hard tasks routinely run many minutes, Simon Willison bluntly calls it 'slow, expensive' - Dual-use safety classifiers misfire on legitimate work: a medical physicist reported fluid dynamics problems and MRI segmentation code refused as biosecurity risks, with requests silently rerouted to Opus 4.8 (the viral HN thread was titled 'If Claude Fable stops helping you, you'll never know'; Anthropic says under 5% of sessions) - Rocky launch: US export controls forced Anthropic to suspend access worldwide from June 12 to June 30, 2026, three days after release, with full restoration only on July 1 Verdict: Take Claude Fable 5 if your workload is genuinely long-horizon: overnight agentic runs, monster migrations, tasks where one multi-hour session replaces days of supervised work. There, the 2x premium over Opus 4.8 pays for itself in task compression, and the benchmarks (80.3% SWE-bench Pro, 11 points clear of the field) are backed by real deployments at Stripe and Cursor. For interactive coding and everyday work, stay on Opus 4.8: 88.6% on SWE-bench Verified at half the price, no classifier misfires, faster turns. Cost-sensitive teams get near-Opus coding from Sonnet 5 at $3/$15 (intro $2/$10 through August 2026). Avoid Fable 5 entirely if your org requires zero data retention or if you work anywhere near biology, medical imaging or security tooling, where the dual-use classifiers still produce false positives and silently swap in Opus 4.8 mid-session. Full review: https://glad-ia-tor.com/tool/claude-fable-5 · Markdown: https://glad-ia-tor.com/tool/claude-fable-5.md ## More Full llm-models ranking: https://glad-ia-tor.com/hall-of-fame/llm-models --- This markdown version exists for AI assistants; the canonical page is https://glad-ia-tor.com/vs/claude-haiku-4-5-vs-claude-fable-5