// head_to_head
Claude Fable 5 vs GPT-5.2
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
Claude Fable 5 scores higher, GPT-5.2 costs less — it depends on your workload.
Claude Fable 5 is ahead by 8.3 points overall, and GPT-5.2 lists 4.2× cheaper per blended million tokens. Whether 8.3 points is worth that depends on how much a wrong answer costs you. GPT-5.2 also leads on measured cost per point of capability, at $0.1289 per point.
anthropic
Claude Fable 5
- Blended / 1M
- $20.00
- Context
- 1M
- Released
- Jun 9, 2026
- Overall score
- 83.0
openai
GPT-5.2
- Blended / 1M
- $4.81
- Context
- 400K
- Released
- Dec 10, 2025
- Overall score
- 74.6
Specs and pricing
| Metric | Claude Fable 5 | GPT-5.2 |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 83.0win | 74.6 |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.7925 | $0.1289win |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $20.00 | $4.81win |
| Input price / 1M | $10.00 | $1.75win |
| Output price / 1M | $50.00 | $14.00win |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $1.00 | $0.175win |
| Context window | 1Mwin | 400K |
| Max output tokens | 128K | 128K |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Fable 5 on top, GPT-5.2 below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | Claude Fable 5 | GPT-5.2 |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $5752.00/mo | $1426.60/mo |
| RAG assistant 8K in / 600 out × 100K requests | $7400.00/mo | $1610.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $6960.00/mo | $1638.00/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $13,300/mo | $2721.25/mo |
| Bulk classification 500 in / 20 out × 5M requests | $25,500/mo | $4987.50/mo |
Which should you pick?
You are running this at volume
GPT-5.2
Lowest measured cost per point of capability at $0.1289 per point — the gap compounds with every request.
Quality matters more than the bill
Claude Fable 5
Highest overall LiveBench score of the two at 83.0.
The workload is coding or agentic work
Claude Fable 5
Leads on agentic coding — 62.2 against 50.3.
You need to fit large documents in one call
Claude Fable 5
Wider context window — 1M against 400K.
Claude Fable 5 vs GPT-5.2 FAQ
Which is better, Claude Fable 5 or GPT-5.2?
Claude Fable 5 scores higher, GPT-5.2 costs less — it depends on your workload. Claude Fable 5 is ahead by 8.3 points overall, and GPT-5.2 lists 4.2× cheaper per blended million tokens. Whether 8.3 points is worth that depends on how much a wrong answer costs you. GPT-5.2 also leads on measured cost per point of capability, at $0.1289 per point.
Is Claude Fable 5 cheaper than GPT-5.2?
GPT-5.2 is cheaper. On a 3:1 input:output blend, Claude Fable 5 lists at $20.00 per million tokens and GPT-5.2 at $4.81 — GPT-5.2 is 4.2× cheaper. Input and output are priced separately — Claude Fable 5 charges $10.00 in and $50.00 out, GPT-5.2 charges $1.75 and $14.00 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Claude Fable 5 vs GPT-5.2: which scores higher on benchmarks?
Claude Fable 5 scores 83.0 and GPT-5.2 scores 74.6 overall on LiveBench, the mean of its seven categories. That is a 8.3-point lead for Claude Fable 5. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.
Which gives better value for money, Claude Fable 5 or GPT-5.2?
GPT-5.2. Cost per point divides the measured dollars LiveBench spent running the benchmark by the score it earned, so it captures something token pricing misses: a reasoning model can emit many times more tokens than its per-token rate suggests. Claude Fable 5 works out at $0.7925 per point and GPT-5.2 at $0.1289.
Does Claude Fable 5 or GPT-5.2 have a bigger context window?
Claude Fable 5 has the larger context window: 1M for Claude Fable 5 against 400K for GPT-5.2. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.
Do Claude Fable 5 and GPT-5.2 support prompt caching?
Both publish a cached-input rate: $1.00 per million for Claude Fable 5 and $0.175 for GPT-5.2, against full input rates of $10.00 and $1.75. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.