# Astra vs Fable: what $20 per million actually buys

- published: 2026-10-05
- read: 6 min
- keywords: GPT-6 Astra vs Claude Fable 5.1, AI model value score, blended price per million tokens, frontier model pricing comparison, capability per dollar, Claude Opus 4.8 pricing
- url: https://rotative.xyz/deep-dive/astra-vs-fable-value
- site: Rotative (rotative.xyz) — evidence-first AI news

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GPT-6 Astra and Claude Fable 5.1 share the most expensive shelf in the index: $10 in, $50 out, a blended $20 per million tokens. On our value score that sticker buys 4.8 capability points per dollar for Astra and 3.3 for Fable 5.1. Claude Opus 4.8, at half the blended price, delivers 8. Muse Spark 1.2, at a 160th of it, delivers 564. The interesting question was never which flagship is better. It is what the premium is actually for, and the index has an answer with numbers on it.

**The short version**

**Verdict: buy the $20 shelf for interactive latency and frontier-only tasks; route everything that scales to the mid-tier, worth up to 117x more capability per dollar.** At identical pricing the index hands Astra every column against Fable 5.1: 96 capability against 65, 93.2 tokens per second against 74.5, 1.05M context against 1M, and the only pareto flag of the two. Read that margin with an asterisk, because the two capability numbers come from different benchmark families.

- **Same price, no tie:** both flagships bill $20 blended. Astra's value score of 4.8 against Fable 5.1's 3.3 is the whole index difference; nothing about the price differentiates them.
- **The premium vs the mid-tier:** Astra costs 2x Opus 4.8, 10x Spark 1.1, 38x Glimmer 30B, and 160x Spark 1.2 contributor rates on blended price.
- **Cost at scale:** 300M tokens in and 60M out per month runs $6,000 on either flagship, $3,000 on Opus 4.8, and $42 on Spark 1.2.
- **The asterisk:** Astra's 96 rides its GPQA column. Fable 5.1's row is thin (GPQA and SWE null, capability sourced from HLE 65), and the same index rates Fable 5, the predecessor, at 79.8. Part of that 31-point gap is measurement, not model.

## the value math

Two conventions do all the work here. Blended price is (3x input + output) / 4, which weights a typical generation mix. Value score is capability divided by blended price: how many index points a dollar buys.

| | gpt-6-astra | claude-fable-5-1 | claude-opus-4-8 | muse-spark-1.2 | muse-glimmer-30b |
|---|---|---|---|---|---|
| org | openai | anthropic | anthropic | muse | muse |
| capability | 96 | 65 | 80 | 70.5 | 60.5 |
| price in / out | $10 / $50 | $10 / $50 | $5 / $25 | $0.10 / $0.20 | $0.30 / $1.20 |
| blended | $20 | $20 | $10 | $0.125 | $0.525 |
| value score | 4.8 | 3.3 | 8 | 564 | 115.2 |
| context | 1.05m | 1m | 1m | 1.05m | 128k |
| throughput | 93.2 tok/s | 74.5 tok/s | 58.8 tok/s | 168.9 tok/s | n/a |
| tier | frontier | mid | frontier | mid | mid |
| pareto | true | false | false | false | false |

Cost per capability point, blended price over capability: Astra $0.21, Fable 5.1 $0.31, Opus 4.8 $0.125, Glimmer 30B $0.0087, Spark 1.2 $0.0018. The flagship sticker is not a rounding error against the mid-tier; it is a 160x spread, and the value scores say the market prices frontier capability like a luxury good: 4.8 points per dollar where the volume tier pays 564. Note what the context column does to the flagship story: Spark 1.2 carries 1.05M context, Astra's own window, at a 160th of the blended price. The premium is not buying context.

One more row matters and is not in the table: Muse Spark 1.1, 62.1 capability at a $2.00 blended standard rate, value 31.1, and 183.8 tokens per second, the fastest speed in this comparison. Spark 1.3 has no capability score yet, so it gets no value claim here.

## where the premium pays

First, the uncomfortable column check: since both flagships cost exactly $20 blended, choosing Fable 5.1 over Astra saves nothing on the index while giving up 31 points of capability, 18.7 tokens per second, and 50K of context. The index flags Astra pareto true, meaning nothing it tracks does Astra's job for less. If you have decided to sit on the $20 shelf, the index gives the round to Astra on every measured column. Matchups this one-sided are rare in a table that usually trades something.

Second, latency where a human is watching. 93.2 tokens per second is 1.25x Fable 5.1 and 1.58x Opus 4.8, and for interactive coding or an agent loop a person stares at, that difference is the product. Note the limit: Spark 1.1 (183.8) and Spark 1.2 (168.9) outrun both flagships, so the latency argument holds only against the frontier class, not against the index at large.

Third, the headroom itself. 96 capability is the top of this index (second place sits at 94.6), and some tasks need the top: the ones where a wrong answer costs more than a month of tokens, or where nothing below 80 capability is trusted to run unsupervised. That customer exists, and for them the value score is the wrong metric by design. Even here, though, honesty about the alternatives: Opus 4.8 offers 80 capability at a $10 blended, value 8, double Astra's points per dollar. The premium over the cheaper frontier is only justified by the last 16 points.

## where it burns

Everywhere tokens scale. Summarization, classification, extraction, log triage, batch pipelines: work where 70.5 capability and 96 capability produce the same business outcome, and the index charges 160x more for the second one. The invoice math makes it concrete. At 300M input and 60M output tokens a month: $6,000 on either flagship, $3,000 on Opus 4.8, $630 on Spark 1.1 standard rates, $162 on Glimmer 30B, $42 on Spark 1.2 contributor rates. The capability given up moving from Astra to Spark 1.2 is 25.5 points; the invoice shrinks by a factor of 143. Context survives the move intact.

The value gap is wider still: 564 against 4.8 is 117.5x, the largest spread in this comparison. And the burn compounds at the low end of difficulty, because classification-shaped work does not use 25 of those 96 points in the first place. Paying for headroom you cannot spend is the definition of a premium with no return.

The routing rule that falls out is unglamorous. Mid-tier for volume, because 117x beats any benchmark argument. Frontier-mid (Opus 4.8 at $10 blended) for work that needs real headroom on a budget. Astra for the interactive frontier where latency and the top of the index both matter. Fable 5.1 for cache-bound agent workloads, where its announced cache pricing, not its capability score, is the reason to pick it.

## the fine print

The capability sources are not the same ruler. Astra's 96 is sourced from its GPQA score; Fable 5.1 has GPQA and SWE null in the index and gets its 65 from an HLE of 65. Strikingly, the same index rates Fable 5, the predecessor, at 79.8 (SWE 95, HLE 64.5), 14.8 points above 5.1 at the same price. Either Anthropic shipped a regression in a point release or the index under-covers 5.1's benchmark set. We cannot tell which from the index alone, which is why the 31-point headline gap should be read as "Astra leads, by less than it looks."

Prices are list rates and the effective bill bends. Anthropic's September 1 announcement put Fable 5.1 at $10/$50 with cache reads cut 75% to $0.25 per million tokens, an estimated 25% saving on typical workloads and up to 45% on agentic ones. OpenAI's pricing page (verified September 22) lists Astra at $10/$50 with $1.00 cached input and 50% off batch. Cache-heavy and batch-shaped bills diverge from any blended formula; our September 10 piece [covered that lane split](/deep-dive/fable-vs-astra) and this one deliberately stays on the blended shelf.

External cross-checks agree on price and disagree on the rest, as usual. Benchlm ranks Astra 88.69, first of 211 models, as of October. The AI Rankings, via a September 19 comparison, flagged that neither lab published a SWE-bench figure for either flagship at launch. Muse Spark 1.3 remains unscored by benchlm (capability null, $0.125 contributor / $2.00 standard), so any value claim about it would be invented, and we do not invent numbers.

Default routing, one line: Spark 1.2-class mid-tier for volume, Opus 4.8 for budgeted frontier work, Astra for the interactive top of the index, and Fable 5.1 only when your own cache math or your own evals say so.