Claude Fable 5 vs GPT-4o mini
Benchmarks, API pricing and specs, head to head. Data updated 2026-06-10.
Anthropic · Jun 2026
The first GA model of Anthropic's Mythos class — a tier above Opus — and the current SWE-bench Verified leader, at $10/$50 per 1M tokens.
OpenAI · Jul 2024
The 2024 budget classic that defined the cheap-LLM tier; GPT-5 nano and mini have since taken its crown.
The verdict
These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: GPT-4o mini works out roughly 76x cheaper per blended million tokens. Claude Fable 5 also takes 1M of context versus 128K for GPT-4o mini.
Specs & pricing
| Claude Fable 5 | GPT-4o mini | |
|---|---|---|
| modhub Index | — | — |
| Input price / 1M | $10 | $0.15 |
| Output price / 1M | $50 | $0.6 |
| Context window | 1M | 128K |
| Max output | 128K | 16K |
| Open weights | no | no |
| Reasoning model | yes | no |
| Multimodal input | text, image | text, image |
| Knowledge cutoff | Jan 2026 | Oct 2023 |
| Released | Jun 2026 | Jul 2024 |
| Example monthly cost* | $175.00 | $2.40 |
* 10M input + 1.5M output tokens per month at list prices, no caching. Green = better value on that row.
Frequently asked questions
- Which is better, Claude Fable 5 or GPT-4o mini?
- These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: GPT-4o mini works out roughly 76x cheaper per blended million tokens. Claude Fable 5 also takes 1M of context versus 128K for GPT-4o mini.
- Which is cheaper, Claude Fable 5 or GPT-4o mini?
- Claude Fable 5 costs $10/$50 per million input/output tokens, while GPT-4o mini costs $0.15/$0.6. For a typical workload of 10M input and 1.5M output tokens per month, that's $175.00 versus $2.40.
- Which model is better for coding, Claude Fable 5 or GPT-4o mini?
- We don't yet track SWE-bench Verified results for both models; check their individual pages for coding-related scores.