GPT-6 vs Grok 4.6: Two Middle Tiers, One Bill That Diverges Above 200K Tokens

GPT-6 Sol and Grok 4.6 cost the same $2.00 per million input tokens and $6.00 per million output tokens at the top of the two columns. What almost nobody prints next to that is that the columns stop matching at different points in the request. Grok 4.6 starts charging its long-context rate once a prompt passes 200,000 input tokens; GPT-6 Sol waits until 272,000. Above those lines the whole request reprices — not just the overflow — and the two vendors reprice it in opposite directions, which is the part that decides a bill for a long agent run. GPT-6 Sol and its siblings GPT-6 Astra and GPT-6 Luna shipped on 22 September 2026; Grok 4.6, the middle tier of SpaceXAI's line, shipped 12 August 2026 and has already been joined by Grok 4.7, so this is a comparison between two shipped models and not a launch of either.

A second thing changed on 7 October 2026 that matters to how you read GPT-6 at all: OpenAI began rolling GPT-6 into ChatGPT's main Chat tab, reaching the free tiers on 8 October, with the Plus, Pro, Business and Enterprise tiers running GPT-6 Sol and the Free and Go tiers running GPT-6 Luna. That is a surface change — the same models, a far larger audience, and a new interface layer OpenAI calls Intelligent UI. It does not move a single API rate. It does mean that if you are benchmarking "GPT-6" against anything, you are now benchmarking against a model that a very large number of people are also talking to in a browser tab.

Where the two cards actually differ

• Short-context input — GPT-6 Sol $2.00 per million vs Grok 4.6 $2.00 per million
• Short-context output — GPT-6 Sol $10.00 per million vs Grok 4.6 $6.00 per million
• Long-request threshold — GPT-6 Sol reprices above 272,000 input tokens vs Grok 4.6 above 200,000
• Long-request input — GPT-6 Sol $4.00 per million vs Grok 4.6 $4.00 per million
• Long-request output — GPT-6 Sol $15.00 per million vs Grok 4.6 $12.00 per million
• Cached input — GPT-6 Sol $0.20 per million vs Grok 4.6 $0.50 per million
• Context window — GPT-6 Sol 1,050,000 tokens vs Grok 4.6 500,000 tokens
• Input modalities — both accept text, image and file
• Knowledge-work score — GPT-6 Sol 47.6 vs Grok 4.6 44.3 on the Artificial Analysis Intelligence Index
• Terminal-Bench 2.1 — GPT-6 Sol not published on the same revision vs Grok 4.6 88.4

Read the two output lines together and the shape of the decision appears. Grok 4.6 is $4.00 cheaper per million output tokens on any request under 200K, and only $3.00 cheaper above it. That is a much smaller gap than the headline 40% suggests, because both models reprice the entire request rather than the portion over the line — a detail worth sitting with, since a prompt at 200,001 tokens is not billed as one token at the expensive rate plus 200,000 at the cheap one.

Then the threshold itself runs the other way. Grok 4.6 begins repricing 72,000 tokens earlier than GPT-6 Sol does. For a workload that sits consistently between 200K and 272K, Grok 4.6 is the more expensive model despite its cheaper per-token headline, and it is the only one of the two that has moved at all. Which side of that window your prompts land on is a more useful question than which headline is lower.

The benchmark gap is smaller and narrower than the price gap

On Artificial Analysis's Intelligence Index, which is a third-party measurement rather than a vendor table, GPT-6 Sol sits at 47.6 and Grok 4.6 at 44.3. A 3.3-point gap on a 0-to-100 scale is real but it is not the kind of distance that makes one model wrong for a task and the other right. It is also measured at a specific reasoning setting per model, and GPT-6 Sol exposes configurable reasoning effort while Grok 4.6 exposes its own — so anyone quoting a single head-to-head number is quoting one point in a two-dimensional grid.

Where the two are genuinely further apart is terminal-style agentic work. On Terminal-Bench 2.1, Grok 4.6 posts 88.4. GPT-6 Sol has no comparable published figure on the revision our catalogue carries, and the honest reading of an empty cell is that the number is not published — not that the model performed badly. If a long-running shell-driven agent is the workload, the published evidence favours Grok 4.6 and the missing evidence does not count as evidence for either side.

The reverse holds on knowledge retrieval at length. GPT-6 Sol records 83.7 on long-context recall against Grok 4.6's 80.3, and both models' vendors report their own figures elsewhere — SpaceXAI highlights GPQA Diamond at 94.9 for Grok 4.6, and OpenAI's GPT-6 material is largely vendor-reported and unreproduced. Two rules keep this straight: a vendor number is a claim, and an index number is a measurement on a named revision. They are not interchangeable and should never be averaged into a single "better" score.

The successor problem

Neither of these is the newest model from its own lab, and pretending otherwise would be the most misleading thing this comparison could do. SpaceXAI shipped Grok 4.7 on 21 September 2026 at the same $2.00 / $6.00 base rate, with the Intelligence Index moving from 44.3 to 46.4. OpenAI shipped GPT-6.1 Sol on 29 September 2026, also at $2.00 / $10.00, with the Intelligence Index at 51.8 and one rate actually improved: cached input fell from $0.20 to $0.10 per million. Artificial Analysis now flags its GPT-6 Sol page as deprecated, pointing readers at GPT-6.1 Sol.

So the fair framing is not "which of these two should you adopt" but "which of these two, and are you sure it is not one generation newer on either side." The reason to stay on GPT-6 Sol is usually a specific eight-day-old integration rather than a capability claim; the reason to stay on Grok 4.6 is a published terminal-agent number that its successor has not yet matched in public. Both are legitimate, and both are time-boxed.

Running both from one key

Both models are routed by OrcaRouter, so the mechanical part of keeping two candidates alive costs nothing: one API in front of 200+ models, the same key, no second contract and no code change between them. That matters more here than usual, because the case for a second model on this particular matchup is not a capability hedge but a routing decision — send the 200K-to-272K window to GPT-6 Sol and everything shorter to Grok 4.6 and the same application gets the cheaper bill on both sides of a threshold that neither vendor lets you choose.

Automatic failover is the boring half of the same setup. Long-context agent runs are long precisely because something is holding a session open, and a provider hiccup at minute forty is the expensive kind of failure. A second route configured in advance turns that into a retry instead of a rerun.

Our catalogue lists both at their provider's own list price, marked up by nothing, so a rate change on either card lands on our side the same day it lands on theirs. That is worth stating plainly rather than as a slogan: the reason to care is that the $0.20-versus-$0.50 cached-input difference above is exactly the kind of line vendors quietly move, and a pass-through means you never have to wait for a reseller to catch up.

What actually decides it

If your prompts are short, Grok 4.6 wins on output price by a margin that no index delta closes, and its terminal-agent score is the strongest published number in either column. If your prompts are long, GPT-6 Sol's later repricing threshold and its longer window are worth more than its higher output rate, and the cached-input line is a quarter of the cost. If your prompts sit between 200K and 272K, you are holding the one workload where the cheaper-looking model is the more expensive one, and the fix is route selection rather than model selection.

The thing to watch is not either model but the two successors already on the shelf. Grok 4.7 and GPT-6.1 Sol both undercut the case for waiting on a decision here, and a comparison that has to be re-run every three weeks is a comparison that belongs behind a router rather than in an architecture document.