// head_to_head

Claude Fable 5 vs GPT-6 Astra

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.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Claude Fable 5 and GPT-6 Astra are close on both score and price.

Neither model separates itself on published score or list price. Pick on the things this table cannot measure: latency under your load, context window headroom, tool-calling reliability, and whichever provider you already have a contract with.

anthropic

Claude Fable 5

Blended / 1M
$20.00
Context
1M
Released
Jun 9, 2026
Overall score
83.0
reasoningtool callingimage inputfile inputprompt caching

openai

GPT-6 Astra

Blended / 1M
$20.00
Context
1.1M
Released
Sep 4, 2026
Overall score
82.2
reasoningtool callingfile inputimage inputprompt caching

Specs and pricing

MetricClaude Fable 5GPT-6 Astra
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

83.082.2
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.7925$0.3942win
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$20.00$20.00
Input price / 1M$10.00$10.00
Output price / 1M$50.00$50.00
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$1.00$1.00
Context window1M1.1M
Max output tokens128K128K

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-6 Astra below, both out of 100.

Agentic coding
62.2
57.3
Coding
86.0
80.4
Reasoning
89.7
92.7
Mathematicstoo close to call
96.0
96.8
Data analysis
80.5
83.0
Language
90.7
89.4
Instruction followingtoo close to call
75.8
75.6

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.

WorkloadClaude Fable 5GPT-6 Astra
Support chatbot

1.2K in / 400 out × 200K requests

$5752.00/mo$5752.00/mo
RAG assistant

8K in / 600 out × 100K requests

$7400.00/mo$7400.00/mo
Coding agent

40K in / 4K out × 20K requests

$6960.00/mo$6960.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$13,300/mo$13,300/mo
Bulk classification

500 in / 20 out × 5M requests

$25,500/mo$25,500/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

GPT-6 Astra

Lowest measured cost per point of capability at $0.3942 per point — the gap compounds with every request.

The workload is coding or agentic work

Claude Fable 5

Leads on agentic coding — 62.2 against 57.3.

Claude Fable 5 vs GPT-6 Astra FAQ

Which is better, Claude Fable 5 or GPT-6 Astra?

Claude Fable 5 and GPT-6 Astra are close on both score and price. Neither model separates itself on published score or list price. Pick on the things this table cannot measure: latency under your load, context window headroom, tool-calling reliability, and whichever provider you already have a contract with.

Is Claude Fable 5 cheaper than GPT-6 Astra?

They cost about the same. Both land near $20.00 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

Claude Fable 5 vs GPT-6 Astra: which scores higher on benchmarks?

Claude Fable 5 scores 83.0 and GPT-6 Astra scores 82.2 overall on LiveBench, the mean of its seven categories. That gap is inside the range that effort settings alone move a score, so treat them as equivalent on published quality. 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-6 Astra?

GPT-6 Astra. 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-6 Astra at $0.3942.

Does Claude Fable 5 or GPT-6 Astra have a bigger context window?

They are effectively the same — 1M for Claude Fable 5 and 1.1M for GPT-6 Astra.

Do Claude Fable 5 and GPT-6 Astra support prompt caching?

Both publish a cached-input rate: $1.00 per million for Claude Fable 5 and $1.00 for GPT-6 Astra, against full input rates of $10.00 and $10.00. 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.
  • ScoresLiveBench 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.