Gemini 4 vs Claude Sonnet 5.5: Identical List Price, 2.7x Different Bill

Gemini 4 Argon ($2.00 per million input tokens, $10.00 per million output) and Claude Sonnet 5.5 ($2.00 per million input tokens, $10.00 per million output) have the same published rate card. Not similar — the same four numbers, on the nose, on both vendors' pricing pages as of 2026-10-14. If you stopped at price you would call this matchup a tie and move on. The bill is not a tie: Artificial Analysis puts the cost of answering one Intelligence Index task at $1.99 for Gemini 4 Argon against $5.46 for Claude Sonnet 5.5, on the same revision of the same ten-evaluation index. A 2.7x gap with identical rates is possible because the two models spend very different numbers of tokens getting to an answer, and that is the whole of this comparison.

Claude Sonnet 5.5 is the mid-tier model A​nthropic shipped on 2026-09-28. Gemini 4 Argon is the only named member of the Gemini 4 line, announced 2026-09-30 and moved to general availability on G​oogle's paid tier on 2026-10-13. This page is for the reader who has both names and is deciding between them, not for someone who needs an introduction to either.

The two rows that separate these models

On Artificial Analysis's Intelligence Index v4.3.2, Gemini 4 Argon at high effort reads 52.56 and Claude Sonnet 5.5 at maximum effort reads 56.00 — displayed as 53 and 56. Sonnet 5.5 is ahead by roughly 3.4 points on a composite of ten evaluations, across the same September-2026 generation window.

Behind that index score is where the money is. Per index task, Argon emits 62,000 output tokens; Claude Sonnet 5.5 emits 197,000, with 147,000 of them reasoning tokens against Argon's 36,000. Run the whole index once and the meter reads $2,407 against $7,260. That is the mechanism, and it explains something the rate card cannot: Sonnet 5.5 answers better and costs more, while the per-token price list says the two are the same product at the same price.

The other axis that decides real work is the output ceiling. A​nthropic publishes 128,000 tokens of synchronous output for Sonnet 5.5. G​oogle publishes an output limit of 1 million tokens for Argon alongside a 1M-token context window — an unusually large decode budget that matters for long-form generation and for agents that write a whole artifact in one pass. Both are billed on output, so the model with the bigger decode ceiling is also the model whose worst case is more expensive on the same input.

What the effort setting does to that comparison

Both figures above are vendor-adjacent measurements at a specific reasoning effort, and effort is a knob, not a fact about a model. Sonnet 5.5 is measured at maximum; Argon at high. Gemini 4 Argon's own pricing page offers Priority, Flex and Batch tiers on top of Standard, and G​oogle's introductory rate on the standard tier doubles on 2026-12-01 — $2.00/$10.00 becomes $4.00/$20.00, which materially changes every number in the paragraph above. Nothing in this comparison survives that date unchanged.

A​nthropic's effort story runs in the opposite direction and is easy to miss in the launch coverage. Sonnet 5.5 shipped at exactly the rates Sonnet 5 carried, and A​nthropic's own migration documentation says effort levels were recalibrated between the two: "An effort level doesn't produce the same amount of thinking as it did on Claude Sonnet 5. Re-run your effort sweep rather than carrying a setting over." So the widely repeated claim that Sonnet 5.5 "costs up to 30% less for most work" is a claim about an operating point you have to choose, not a price you inherit. Artificial Analysis measures the same model at maximum effort costing roughly 49 per cent more per task than its predecessor, which is the other end of the same curve.

If you are running the Claude line, that recalibration is cheap to absorb: all four current tiers are in one catalogue at list price with 0% markup added, so moving between Claude Sonnet 5.5, Claude Opus 5.5 and Claude Haiku 5.5 is a model-string change on one key rather than a second contract. Nothing on the Gemini 4 stem is in that catalogue as of 2026-10-14 — Gemini 4 Argon is reachable through G​oogle's own API and other third-party platforms, not through us — so a reader who wants a fallback path behind Argon has to build it outside our routing.

Where the two vendors' published material actually differs

A​nthropic documents Claude Sonnet 5.5 down to the lifecycle: model ID claude-sonnet-5-5, 1M-token context, 128,000-token synchronous output rising to 300,000 behind a beta header on the Batches API, adaptive thinking on by default at high effort, knowledge cutoff June 2026, and a retirement commitment of not sooner than 2028-09-28 on A​nthropic-operated platforms. Amazon Bedrock and G​oogle Cloud set their own dates. The ID is a pinned snapshot, so it will not drift under you.

G​oogle's documentation for Gemini 4 Argon is thinner and the gap is the tell. The model page carries the ID gemini-4-argon, the Stable badge, a unified 1M-token context and a 1M-token decode ceiling; the pricing page carries four service tiers and the December step-up. What is not there is the surrounding tier structure. There is one Gemini 4 model, so there is no cheaper rung to fall back to when the flagship is overkill and no dearer rung to reach for when it is not enough. A​nthropic's line has four; G​oogle's generation 4 has one, and the Pro and Flash slots on G​oogle's own site are still occupied by Gemini 3.x models.

G​oogle's launch benchmark table, which shows Argon leading Sonnet 5.5 on most rows, is vendor-reported, and G​oogle's methodology discloses that the non-G​oogle columns are the competitors' own self-reported figures rather than runs G​oogle performed. Treat it as a statement of what G​oogle claims. The Artificial Analysis rows above are the independent measurement, and they are the ones this page leans on.

Choose by workload, not by verdict

Reach for Claude Sonnet 5.5 when the task is well-scoped production work where a wrong answer costs more than a token does — the coding and reasoning rows on the independent index favour it, its documentation is complete enough to plan against, and it carries a published retirement floor two years out. Its practical trap is the effort default: carrying a Sonnet 5 effort setting straight over will produce a bill that looks nothing like the launch coverage promised.

Reach for Gemini 4 Argon when throughput and per-task cost dominate and the workload is the kind that produces short, dense answers — extraction, classification, high-volume agent steps. Its advantage is structurally in token economy rather than in the rate card, which is why it holds up on cost per task even though the headline price is identical to Sonnet 5.5's. Its practical traps are the December rate step and the absence of a cheaper sibling.

The one fact that decides most of these evaluations: identical rates do not mean identical bills, and the difference here is a 62,000-token answer versus a 197,000-token one. Measure your own workload's output length before you pick, because that single number moves the cost more than the price list does.

Where the comparison meets a key

Both of these are on our key at provider list price with 0% markup added, which is worth more here than in most matchups: the cost argument on this page turns on effort settings and cache-hit ratios rather than on the sticker price, and re-running the same prompt against Claude Sonnet 5.5 and Gemini 4 Argon from one endpoint is how you settle it with your own numbers instead of ours.

The tier above this one is priced on its own page. Claude Opus 5.5 It is the same contract, the same SDK and the same key.

A model choice is also a question of what has gone wrong before: the documented AI incidents and agent failures for models of this class are collected in the OrcaRouter AI Incident Archive , where each entry carries its own sources, severity, confidence grade and disputed flag.