GPT-6 Astra vs Grok 4.6: The Index Tie Broke, and the Price Gap Depends on the Tier

GPT-6 Astra and Grok 4.6 were level on the one independent scoreboard that ranks both when this page first ran on 4 September 2026. That is the sentence the page has to take back. Read against the Artificial Analysis Intelligence Index as it stands on 16 September 2026 — version v4.3, ten evaluations — GPT-6 Astra (max) sits at 53 and Grok 4.6 (high) at 44, where there used to be a tie. The other correction is the one in the headline you clicked. Open​AI's rate card, read the same day, lists GPT-6 Astra at $10.00 per million input tokens, $1.00 per million cached input and $50.00 per million output; x​AI's card lists Grok 4.6 at $2.00, $0.50 and $6.00. Against standard input that is five times. Against output it is 8.3 times. Against cached input — the line most production traffic actually bills against — it is twice. There is no single multiplier, and the version of this page that claimed one was rounding a four-row rate card into a slogan. This is a refresh, not a launch: GPT-6 Astra is Open​AI's flagship from 3 September 2026 and Grok 4.6 is x​AI's from 12 August 2026. What has moved since is the measurement, the availability and the arithmetic.

The multiplier was never one number

Start with the two rate cards as their vendors publish them on 16 September 2026, because everything downstream inherits their tier shapes. Open​AI documents GPT-6 Astra at $10.00 per 1M input tokens, $1.00 per 1M cached input, $12.50 per 1M cache writes and $50.00 per 1M output, and splits the card into short-context and long-context columns; past the long-context threshold — 272,000 input tokens on the figures reported for this card — the whole request reprices to $20.00 in, $2.00 cached and $75.00 out. Batch and Flex bill at half the standard rates, Fast mode at double. x​AI documents Grok 4.6 at $2.00 per 1M input, $0.50 cached and $6.00 output against a 500,000-token context window, and once a request reaches 200,000 prompt tokens the entire request is billed at $4.00 in, $1.00 cached and $12.00 out. Those are vendor rate cards, not measurements.

Put them side by side and the old headline multiple decomposes. Standard input: $10.00 against $2.00, five times. Output: $50.00 against $6.00, 8.3 times. Cached input: $1.00 against $0.50, twice. Long-context input: $20.00 against $4.00, five times again — but long-context output is $75.00 against $12.00, or 6.25 times. The five in the old title was not invented. It was one row of a four-row card wearing a slogan's clothes, and which row you quote changes the answer by a factor of four. Anyone giving you one number for this matchup is choosing a tier and not telling you which.

There is a second reason per-token arithmetic under-describes this pair, and it cuts the other way. The two models do not spend the same number of tokens to finish the same work, and on Artificial Analysis's cost-per-task measure — the weighted average cost of running its Intelligence Index evaluation — the expensive-per-token model is the cheaper one per finished job, once you match the effort settings. Read from AA's own model data on 16 September 2026, GPT-6 Astra at high effort comes in at $1.72 per index task against Grok 4.6 at high on $1.86. The reason is in the token counts on the same record: Astra burns 60M output tokens to run the full index against Grok 4.6's 94M, and 27k output tokens per task against 36k. Five times the input rate, at roughly two-thirds the token spend, lands slightly ahead.

The headline pairing on AA's own comparison page says something different, and both are true. AA's page leads with GPT-6 Astra at max — $3.26 per task, 53 on the index — set against Grok 4.6 at high, $1.86 and 44. Read that way, the premium looks like it buys nothing on cost. Read at matched high effort, Astra is 51 on the index against 44 and a dime cheaper per task. Which figure belongs in your budget depends entirely on whether you intend to run Astra at max or at high, and AA's page does not make you choose. That is the same failure as the old title's single multiplier, one level down.

The index tie is gone, and the honest reading is narrower than it looks

When this page was first written, both models sat at 61 on the Artificial Analysis Intelligence Index and the whole article turned on price. That finding no longer reproduces. On the board as read on 16 September 2026, GPT-6 Astra (max) is at 53 and Grok 4.6 (high) at 44. Both models publish a full effort ladder, and the ladder matters more than the single row AA prints on its comparison page: from AA's own model data, GPT-6 Astra runs 53 (max), 53 (xhigh), 51 (high), 50 (medium), 46 (low), and Grok 4.6 runs 44 (high), 44 (xhigh), 43 (medium), 35 (low). At the closest matched setting, high against high, the gap is seven points.

Two cautions belong in the same breath. First, the index was re-cut: the version live now is v4.3, built from ten evaluations — AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience and AA-LCR v1.1 — over a different model population than the early-September board. Part of a nine-point gap appearing is recalibration rather than either lab shipping something new, and a reader comparing this page to the last one is comparing two different rulers. Second, the two entries are not matched effort settings: AA's comparison pairs Astra's max with Grok 4.6's high, and a max-against-high comparison is not like-for-like. The safe reading of a nine-point spread on an index that bundles ten evaluations is a real but modest separation, not a rout — several models cluster within a few points either side of both. What can be said is the reverse of what this page used to say: on the independent scoreboard these two are no longer interchangeable, and the more expensive one is ahead.

Speed, which the earlier version of this page had to leave blank for Astra, is now measured — and the latency figures are the more striking half. Artificial Analysis times GPT-6 Astra (max) at 52.9 output tokens per second against Grok 4.6 (high) at 57.7, a gap you can feel on a long generation and not one that should reshape a routing decision. Time to first token is a different story: 334.04 seconds for Astra against 38.63 for Grok 4.6, and end-to-end response time 343.48 seconds against 47.31. Astra thinks for minutes before it answers. For batch and overnight agent work that is invisible; for anything interactive it is the deciding number, and it is nowhere on either rate card.

Astra's own benchmark sheet, and who is allowed to say what

Open​AI's headline figures for GPT-6 Astra, all vendor-reported and none of them reproduced here: 98% on FrontierMath Tier 4, 100% on ExploitBench — against 78.5% for Open​AI's previous flagship, GPT-5.6 Sol — and 99.9% on ARC-AGI-3. These are the numbers the launch coverage repeated, and two of them deserve more scepticism than they got.

ARC-AGI-3 first. The 99.9% comes from Open​AI's provider-adapter harness. ARC Prize, which runs the benchmark, separately measured 62.7% for the same model under its provider-neutral Standard harness, at $26,098 for the run. ARC Prize's own note is that the adapter preserves Open​AI's reasoning state between requests, so the two figures measure different things and should never be quoted as though they were the same measurement. The magnitude of the difference makes the point better than any argument: Astra at "none" reasoning under the adapter scores 96.7%, roughly 34 points above its own max-reasoning score under the Standard harness. The second figure is the harness doing work the model did not.

FrontierMath Tier 4 is the other one. The 98% is Open​AI's own report on a benchmark whose development Open​AI funded; at least one comparison table from launch week prints 97.6% for the same result. Treat both as vendor-reported and neither as settled.

What survives the harness argument is worth keeping. ARC Prize also found that Astra used fewer actions than the median tested human on 96% of the levels it completed, averaging 51.7% fewer actions per level against a human baseline drawn from roughly 500 participants — an efficiency result that does not depend on the adapter. And ARC Prize said plainly that it is not claiming Astra is AGI: the environments are bounded and deterministic, and saturating a benchmark is not proof of general capability. On the independent coding side, Datacurve's DeepSWE v1.1 — 113 tasks across 91 active open-source repositories — lists GPT-6 Astra at 74.1%. That is a strong result rather than a separated one; the top of that board is a cluster, and a board whose leading entries fall within a couple of points of each other is a board about uncertainty as much as about capability. No Grok 4.6 figure at a comparable setting was published on it at the time of writing, so this dimension has one side.

Two ways of working, and a real difference in control

Even where a score is close, these two do not agree on how you steer them. Grok 4.6 is a single strong model with an explicit reasoning-effort dial; you decide how much thinking a request deserves and you pay a flat rate for it. GPT-6 Astra runs longer on its own and is built to pause for review before it commits. It is also the first Open​AI model the company has rated "critical" under its Preparedness Framework for cybersecurity risk — a vendor self-assessment, not an external finding — and Open​AI itself concedes that its monitorability has decreased relative to its previous flagship, which is why the most permissive settings are gated to vetted partners rather than sold openly. For a security team, that gating is a feature. For a developer who wants deterministic, steerable output on a deadline, it is friction you are paying a premium to acquire.

The scoreboard, labeled

• Intelligence (independent) — matched effort, high against high: GPT-6 Astra 51, Grok 4.6 44. As AA's comparison page pairs them, Astra (max) 53 against Grok 4.6 (high) 44. Artificial Analysis Intelligence Index v4.3, read 16 September 2026. Not level; the size of the gap depends on the pairing.

• List price, standard tier (vendor rate cards, read 16 September 2026) — GPT-6 Astra $10.00 in / $50.00 out / $1.00 cached per 1M. Grok 4.6 $2.00 in / $6.00 out / $0.50 cached per 1M. Five times on input, 8.3 times on output, twice on cached input.

• List price, long context (same cards, same date) — GPT-6 Astra: whole request repriced past the long-context threshold at $20.00 / $2.00 / $75.00. Grok 4.6: whole request repriced at 200K prompt tokens to $4.00 / $1.00 / $12.00.

• Cost per task (independent) — matched effort, high against high: GPT-6 Astra $1.72 per Intelligence Index task, Grok 4.6 $1.86. As AA's comparison page pairs them, Astra (max) $3.26 against Grok 4.6 (high) $1.86. Artificial Analysis, read 16 September 2026.

• Latency (independent) — GPT-6 Astra: 334.04s to first token, 343.48s end to end. Grok 4.6: 38.63s and 47.31s. Artificial Analysis, read 16 September 2026. The widest gap on this page. OrcaRouter's own listing for the same model records a p50 time to first token of 6.71s and a p95 of 10.00s over seven days, which measures a different point in the response and is not comparable to AA's figure — do not put the two in the same sentence as though they were.

• Speed (independent) — GPT-6 Astra 52.9 output tokens/s at max. Grok 4.6 57.7 tokens/s at high. Artificial Analysis, read 16 September 2026.

• Agentic coding (independent) — GPT-6 Astra 74.1% on Datacurve's DeepSWE v1.1. No comparable Grok 4.6 run was published on the same board at the time of writing, so this dimension has one side.

• Cyber and reasoning (vendor-reported) — GPT-6 Astra: FrontierMath Tier 4 98%, ExploitBench 100%, ARC-AGI-3 99.9% on Open​AI's provider adapter, against ARC Prize's independently measured 62.7% on its Standard harness. Open​AI-reported; not reproduced here.

• Access today — both models are callable through OrcaRouter on one key. Router-listed rates, read 16 September 2026: GPT-6 Astra at $10.00 / $50.00 per 1M with a 1.05M-token context, Grok 4.6 at $2.00 / $6.00 per 1M with a 500K-token context.

One note about the graphics on this page, because they carry numbers the text qualifies. The hero card and the scoreboard print the same pairing Artificial Analysis leads with — GPT-6 Astra at its max reasoning setting against Grok 4.6 at high — so the scoreboard's intelligence row reads the max-effort score while its cost row reads the high-effort cost. Both figures are AA's, both are current, and they are not from the same effort setting. The text above gives the matched-effort pair wherever the difference matters. The earlier version of this page carried four graphics built on the 61-versus-61 index reading; they have been replaced rather than annotated, because a hero card asserting a claim the article retracts is worse than no hero card.

Availability changed, and it changes the routing answer

The first version of this page had to report that GPT-6 Astra was not on OrcaRouter and Grok 4.6 was. Both are in the catalog now — GPT-6 Astra under the model id openai/gpt-6-astra at Open​AI's list rates, Grok 4.6 under grok/grok-4.6 at x​AI's. OrcaRouter-listed rates, read 16 September 2026. The Astra endpoint is not a catalogue entry either: the same listing records 180.7M tokens of traffic over the previous seven days, router-listed, read the same day.

That matters for this matchup specifically, because the two cards have different tier shapes. A router that bills the provider's list price with 0% markup applies whichever tier the request actually lands in: an Astra call that stays under the long-context threshold is not repriced by our side, and a Grok 4.6 call that crosses 200K is repriced by x​AI's rule and not ours. Every rate on our side is passed through at 0% markup — the vendor's number is the number you pay, and when a vendor changes it the change is live on the same key the same day. With both models on one key, splitting a workload between them, Astra on the hard autonomous work and Grok 4.6 carrying volume, is a routing change rather than a second contract; automatic failover means a rate limit on one path is a routing event instead of an outage; and the routing DSL lets you compose the two into a single call when you want the cheap model to draft and the expensive one to check.

Who should pay the premium

Buy GPT-6 Astra if your work sits in the band where it is now measurably ahead. The independent index separates it from Grok 4.6 at the settings AA publishes, its DeepSWE v1.1 result is a real independent number, and the vendor's own benchmark sheet is genuinely frontier once the harness caveats are attached. Budget on a per-task basis rather than a per-token one, and watch the long-context threshold, which is where a single request stops being an expensive call and becomes a very expensive one. Buy Grok 4.6 if you want frontier-adjacent reasoning at a rate that survives a real budget, plus the faster measured output of the two and a pricing structure with one cliff rather than two.

The corrected summary of this matchup is not that a five-fold gap buys nothing, and not that the two are level. It is that the gap is real at every tier and the ratio depends on the tier you read; that the performance gap is now real as well; and that the two point in the same direction — which is the opposite of what this page said on 4 September 2026, and a better reason to choose between them than a slogan about multiples.