Gemini 4 Hydrogen vs Claude Haiku 5.5: A 15x Price Gap That Shrinks to 7x Per Finished Task

On the rate card the gap is absurd. Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output for prompts up to 100,000 tokens; G​emini 4 Hydrogen costs $1.50 and $7.50. That is fifteen times more expensive on both lines, for a model that only entered G​oogle's catalogue on 12 November 2026. Nobody choosing between them this week is choosing between two prices, though. They are choosing between a model that scores 54 on the Artificial Analysis Intelligence Index and one that scores 36, and the fifteen-times figure dissolves the moment you measure what each one costs to finish a job rather than to start one.

The per-token number and the per-task number disagree by half

Artificial Analysis runs both models through the same harness and publishes cost per completed index task alongside the per-token price. The results are not close to what the rate cards suggest.

• Per-token, input and output — G​emini 4 Hydrogen $1.50 / $7.50 vs Claude Haiku 5.5 $0.10 / $0.50. Haiku is 15.0x cheaper on input and 15.0x cheaper on output, flat.

• Per completed index task — G​emini 4 Hydrogen $3.16 at its highest thinking setting vs Claude Haiku 5.5 $0.41. Haiku is 7.7x cheaper, not 15x.

• Why the gap halves — verbosity. Haiku 5.5 generated 298 million output tokens to work through the index, against 107 million for the median model in its own comparison class — Carbon and Hydrogen are measured against a 72.8-million median, so the two medians are not the same yardstick. It is cheap per token and expensive per answer, because it takes many more tokens to reach one.

• Blended rate on the same 7:2:1 cache/input/output mix — G​emini 4 Hydrogen $1.10 per million vs Claude Haiku 5.5 $0.077 per million.

Read the last two lines together and the pricing argument changes shape. A team that budgets from the rate card will expect a fifteen-fold saving and get a little under eight. A team that budgets from cost-per-task gets the real number, and that number is still overwhelmingly in Haiku's favour — but it is a number you can plan against, which the rate card is not.

There is a threshold buried in Haiku's card that neither figure captures. Everything above is the sub-100K-token price. Past 100,000 tokens of prompt, Haiku 5.5 moves to $0.50 input and $2.50 output — a five-fold jump that lands it at exactly a third of Hydrogen's output price rather than a fifteenth. Both models hold a 1,048,576-token window, so the crossover is reachable rather than theoretical: a long-context workload puts Haiku at $0.50/$2.50 against Hydrogen's $1.50/$7.50, and the per-token gap narrows to 3x while the capability gap stays exactly where it was.

What eighteen index points buy, in the tasks people actually run

Eighteen points of index is a large gap on paper. Whether it is a large gap in practice depends entirely on the shape of the work, and the vendor benchmarks point in different directions depending on which one you read.

• Agentic terminal work — G​oogle reports G​emini 4 Hydrogen at 57.0% on Terminal-Bench 4.1, labelled cheating-adjusted. A​nthropic reports Claude Haiku 5.5 at 39.2% on Terminal-Bench 4.0. Different versions of the benchmark, so the comparison is directional rather than exact, but the direction is consistent and it favours Hydrogen by a wide margin.

• Computer use — Hydrogen at 77.6% on OSWorld-2.1, vendor-reported; Haiku 5.5 at 72.4% on the offline subset of the same benchmark, also vendor-reported. A narrower Hydrogen lead, and the subset qualifier means the two figures are not measuring quite the same thing.

• Hard reasoning without tools — Hydrogen at 58.8% on HLE-Diamond; Haiku 5.5 at 45.9% on Humanity's Last Exam with no tools, rising to 57.4% with tools. This is the widest honest gap in the pair, and it is the one that maps to "can this model hold a hard problem without a scaffold".

• Code review and repair — Hydrogen at 66.6% on Chartography; Haiku 5.5 at 46.4% on Chartography with no tools. Twenty points, same benchmark name, same no-tools condition.

• Frontier coding — A​nthropic reports Haiku 5.5 at 46.4% on FrontierCode 1.1, and reports a 66.2 FrontierCode score from Cognition when Haiku 5.5 runs as a sidekick inside Devin Fusion. Note the second number is a different arrangement, not a different score for the same task, and A​nthropic labels both as customer-reported rather than first-party.

Every figure above is vendor-reported by the company that sells the model. None has an independent reproduction, and the benchmark versions differ enough that adding them up into a single "Hydrogen is X% better" claim would be dishonest. What they support is narrower and more useful: Hydrogen is substantially better at the tasks that run for a long time and use tools; the gap is smallest where the job is a single bounded question.

Both of them are slow to start, which nobody puts in the headline

This is the part of the comparison that surprises people who chose on price or on index and then watched the first token arrive.

• Time to first answer token — G​emini 4 Hydrogen 40.55 seconds at its highest thinking setting vs Claude Haiku 5.5 175.95 seconds at its highest setting. Hydrogen starts four times sooner, and both numbers are far above what an interactive surface tolerates.

• Output speed once it starts — Claude Haiku 5.5 256 tokens per second vs G​emini 4 Hydrogen 188 tokens per second. Haiku writes faster and starts later.

• Average time per index task — Claude Haiku 5.5 14.7 minutes. The two models end up in similar territory per completed task; they get there by opposite routes.

• At Hydrogen's default thinking level the first-token figure drops to roughly 16.7 seconds, which is the number that matters for a chat surface, and which is also the setting that produces the 51 index score rather than the 54.

If you are building anything a human waits on, neither model's headline configuration is appropriate. Haiku 5.5 in particular is an adjustable-effort model — Low through Max — and the 175.95-second and index-36 figures are the Max setting. At lower effort it starts sooner and scores lower, and A​nthropic publishes no table mapping one to the other. That is a test you have to run yourself.

Caching is where the price ratio actually lives

For any workload with a stable prefix — a system prompt, a repository map, a document set — cached input is most of the bill, and the two cards behave differently enough to reorder the comparison.

• Cache read price — Claude Haiku 5.5 $0.01 per million, a 90% discount on its $0.10 input rate. G​emini 4 Hydrogen $0.075 per million, a 95% discount on its $1.50 rate.

• Cache mechanism — Claude Haiku 5.5 supports explicit cache writes at $0.125 per million, so you control what is cached and for how long. G​emini 4 Hydrogen supports implicit caching only, with no explicit cache handles, so the discount is a behaviour of the service rather than an API you call.

• What that means — a workload with a 60,000-token shared prefix read a thousand times a day costs $0.60 a day in cache reads on Haiku and $4.50 on Hydrogen, a 7.5x gap rather than 15x, because Hydrogen discounts 95% where Haiku discounts 90%. Push the same prefix to 200,000 tokens, past Haiku's threshold, and the picture inverts: Haiku's long-tier cache read is $0.05 per million, so the read costs $10.00 on Haiku against $15.00 on Hydrogen, while every fresh input token in that request is now three times cheaper on Haiku. The cache gap narrows exactly where the input gap widens, which is not the trade a long-context workload expects.

The asymmetry matters most for the workload Hydrogen is best at. Long agentic sessions with a large stable context are exactly where implicit caching helps and exactly where you would want explicit control over what stays resident. Haiku gives you the control and the cheaper cache at every prefix length; Hydrogen gives you the capability and asks you to trust the service to notice the repetition.

Three workloads, three different answers

Abstracting further would be a disservice, so here is where the line falls in practice.

A classification or extraction pipeline over millions of short documents is Haiku 5.5's workload and not close. Bounded input, bounded output, no tools, no long horizon: the index gap is irrelevant because the task does not exercise it, and $0.10/$0.50 against $1.50/$7.50 is a fifteen-fold saving on a bill that is already the dominant cost. Moving this to Hydrogen buys nothing and costs an order of magnitude.

A coding agent that edits files, runs tests and recovers from failures is Hydrogen's workload. The Terminal-Bench and Chartography gaps are the direct evidence, and the cost-per-task figure — $3.16 against $0.41 — understates the difference, because a task Haiku cannot finish has an infinite cost per completion rather than a cheap one. The comparison only holds for tasks both models can do.

An overnight batch that summarises long documents sits in the ambiguous middle and is decided by the 100K threshold. Under 100,000 tokens per call, Haiku is fifteen times cheaper per token and roughly eight times cheaper per completed task. Over it, Haiku's price quintuples and the honest answer is to test both on your own corpus, because the crossover depends on how much of your input is prompt versus document.

An interactive assistant is neither. Both models are too slow to start at their maximum settings, and the right configuration for a chat surface is Hydrogen at its default level or Haiku at a lower effort setting — a comparison of two downgrades, which almost nobody benchmarks and which is the only version of this question that reaches a user.

Running both without picking a winner in advance

The sensible position for most teams is that this is not a migration but a routing decision, and routing decisions are cheaper to reverse than migrations.

OrcaRouter carries neither of these two models at the top of their range: Claude Haiku 4.5 is in the catalogue at $1.00 and $5.00 per million with a 200,000-token window, and Gemini 3.8 Flash at $0.75 and $3.75 with the full 1,048,576-token window — both at provider list price with 0% markup, on one key, with automatic failover across providers. Haiku 5.5 and Hydrogen both come from their vendors' own APIs. So the workable arrangement is a routing policy: Hydrogen called direct for the long-horizon execution turns where its benchmark lead is real, Haiku 5.5 called direct for the high-volume bounded calls where its price is real, and a routed model behind both as the path a request falls back to when either vendor throttles, raises a rate limit, or ships a price change.

That last clause is not hypothetical. G​oogle's card already schedules Gemini 4 Carbon and Gemini 4 Argon to double on 1 December 2026, from $2.00/$10.00 to $4.00/$20.00, while Hydrogen carries no dated step. A​nthropic has moved Haiku's price once already this cycle, cutting it roughly 90% at the sub-100K tier when 5.5 replaced 4.5. A routing layer that passes provider list price through with no markup means those changes reach you on the day they land rather than at the next contract renewal — which, for a comparison whose entire argument is price, is the feature that matters.

What would change this answer

Three things, in order of how much they would move it.

An independent reproduction of the Terminal-Bench gap. Every agentic figure above is vendor-reported on both sides, on different benchmark versions, and the single largest justification for Hydrogen's price premium rests on numbers neither company has had audited. Artificial Analysis publishes an index for both models but not the per-benchmark subscores that would settle it.

A published effort-to-quality curve for Haiku 5.5. If Low effort holds most of the Max-setting score at a fraction of the latency, the interaction case narrows and the price advantage spreads upward into workloads currently assigned to Hydrogen. A​nthropic ships the setting and not the table.

A move on Hydrogen's card. It currently has none, which is unusual in a family where two of three members double in three weeks. If that changes, the cost-per-task figure — the one number that makes this comparison interesting — moves with it, and the 7.7x becomes something else entirely.

Until one of those lands, the defensible summary is the one the independent harness supports rather than the one the rate card implies: Haiku 5.5 is between seven and fifteen times cheaper depending on whether you count tokens or finished tasks, Hydrogen is decisively better at anything that runs long and uses tools, and the only number that should decide the split is what each costs you per task you can actually complete.