# Claude Haiku 4.5 vs Claude Opus 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-opus-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 Opus 5 |
|---|---|---|
| Price | $5/1M out | $25/1M out |
| Crowd score | 67% (2 votes) | 63% (4 votes) |
| provider | Anthropic | Anthropic |
| contextWindow | 200K tokens | 1M tokens |
| priceIn | $1/1M in | $5/1M in |
| priceOut | $5/1M out | $25/1M 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 |
| speed (1-5) | 4.5 | 2 |
| valueForMoney (1-5) | 4 | 4 |

### 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 Opus 5

> Anthropic's July 2026 Opus refresh: near-Fable 5 intelligence at half the price, same $5/$25 as Opus 4.8

Strengths:
- Ranked #1 in composite intelligence across 190 models on Artificial Analysis at launch, and 43.3% on Frontier-Bench v0.1 vs 34.4% for GPT-5.6 Sol and 33.7% for Claude Fable 5
- 3.9x better than GPT-5.6 Sol on ARC-AGI-3 novel reasoning (30.2% vs 7.8%), and Elo 1861 on GDPval-AA v2 economic knowledge work, ahead of Fable 5 (1747)
- 79.2% on SWE-bench Pro, within a point of Fable 5 (80.0%) and 10 points above Opus 4.8 (69.2%), at half Fable's price; Cursor's co-founder calls it 'near Fable 5 intelligence at Opus speed and cost'
- Same $5/$25 pricing as Opus 4.8 with a bigger window: 1M context is now the default and only tier, with 128K max output and prompt caching from 512 tokens

Weaknesses:
- Notably slow and very verbose: 52.6 output tokens/s and 68 seconds to first token on Artificial Analysis, and it consumed ~100M output tokens during their eval vs a 63M median
- The verbosity is a real-world cost problem: CodeRabbit measured it reading ~50% more and writing ~65% more than reference frontier models per code-review call
- No actual price cut despite the 'cost-efficient' narrative: identical to Opus 4.8 ($5/$25), nearly GPT-5.6 money ($5/$30), and more than 2x comparable Gemini or Grok tiers

Verdict: Claude Opus 5 is the sane default of the Series 5 range: most of Fable 5's intelligence (and more than Fable on Frontier-Bench and GDPval) at exactly half the token price, with classifiers that trigger 85% less often. If you migrated workloads to Fable 5 for capability but resent the bill or the false-positive refusals, move them here; if you are still on Opus 4.8, the upgrade is 10 SWE-bench Pro points for free. The two honest reasons to look elsewhere: latency and verbosity. At 52.6 tokens/s with 68s to first token it is a poor fit for interactive UX, and its token appetite quietly inflates real costs beyond the sticker price, so budget-sensitive high-volume pipelines still belong on Sonnet 5, Gemini or DeepSeek. Keep Fable 5 only for the longest autonomous runs where its slight SWE-bench Pro edge compounds.

Full review: https://glad-ia-tor.com/tool/claude-opus-5 · Markdown: https://glad-ia-tor.com/tool/claude-opus-5.md

## More

Full llm-models ranking: https://glad-ia-tor.com/hall-of-fame/llm-models

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