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Claude Sonnet 5.5 vs Gemini 4 Hydrogen

Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Effectively the same quality — Gemini 4 Hydrogen is the cheaper way to get it.

The two are within 0.0 points overall, which is inside the range that effort settings alone move a LiveBench score, so treat them as quality-equivalent. Gemini 4 Hydrogen lists 33% cheaper per blended million tokens. When quality ties, cost is the whole decision. Gemini 4 Hydrogen also leads on measured cost per point of capability, at $0.0192 per point.

anthropic

Claude Sonnet 5.5

Blended / 1M
$4.00
Context
1M
Released
Sep 28, 2026
Overall score
77.0
reasoningtool callingimage inputfile inputprompt caching

google

Gemini 4 Hydrogen

Blended / 1M
$3.00
Context
1.0M
Released
Nov 12, 2026
Overall score
77.0
reasoningtool callingaudio inputfile inputimage inputvideo inputprompt caching

Specs and pricing

MetricClaude Sonnet 5.5Gemini 4 Hydrogen
LiveBench overall

Weighted mean of the seven LiveBench category scores, 0–100. Higher is better.

77.077.0
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.0580$0.0192win
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$4.00$3.00win
Input price / 1M$2.00$1.50win
Output price / 1M$10.00$7.50win
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.100$0.075win
Context window1M1.0M
Max output tokens128K944Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Sonnet 5.5 on top, Gemini 4 Hydrogen below, both out of 100.

Long-horizon agentic
63.4
61.8
Coding
77.2
78.5
Reasoning
91.6
88.6
Browser
89.3
77.1
Data analysis
59.5
83.2
Research
88.0
86.8
Documents & design
81.3
77.3

What each one costs to run

Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.

WorkloadClaude Sonnet 5.5Gemini 4 Hydrogen
Support chatbot

1.2K in / 400 out × 200K requests

$1,143/mo$857.40/mo
RAG assistant

8K in / 600 out × 100K requests

$1,440/mo$1,080/mo
Coding agent

40K in / 4K out × 20K requests

$1,336/mo$1,002/mo
Document extraction

20K in / 1.5K out × 50K requests

$2,655/mo$1,991/mo
Bulk classification

500 in / 20 out × 5M requests

$5,050/mo$3,787/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

Gemini 4 Hydrogen

Lowest measured cost per point of capability at $0.0192 per point — the gap compounds with every request.

The workload is coding or agentic work

Claude Sonnet 5.5

Leads on long-horizon agentic — 63.4 against 61.8.

Claude Sonnet 5.5 vs Gemini 4 Hydrogen FAQ

Which is better, Claude Sonnet 5.5 or Gemini 4 Hydrogen?

Effectively the same quality — Gemini 4 Hydrogen is the cheaper way to get it. The two are within 0.0 points overall, which is inside the range that effort settings alone move a LiveBench score, so treat them as quality-equivalent. Gemini 4 Hydrogen lists 33% cheaper per blended million tokens. When quality ties, cost is the whole decision. Gemini 4 Hydrogen also leads on measured cost per point of capability, at $0.0192 per point.

Is Claude Sonnet 5.5 cheaper than Gemini 4 Hydrogen?

Gemini 4 Hydrogen is cheaper. On a 3:1 input:output blend, Claude Sonnet 5.5 lists at $4.00 per million tokens and Gemini 4 Hydrogen at $3.00 — Gemini 4 Hydrogen is 33% cheaper. Input and output are priced separately — Claude Sonnet 5.5 charges $2.00 in and $10.00 out, Gemini 4 Hydrogen charges $1.50 and $7.50 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Claude Sonnet 5.5 vs Gemini 4 Hydrogen: which scores higher on benchmarks?

Claude Sonnet 5.5 scores 77.0 and Gemini 4 Hydrogen scores 77.0 overall on LiveBench, the weighted mean of its seven categories. That gap is inside the range that effort settings alone move a score, so treat them as equivalent on published quality. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.

Which gives better value for money, Claude Sonnet 5.5 or Gemini 4 Hydrogen?

Gemini 4 Hydrogen. Cost per point divides the measured dollars LiveBench spent running the benchmark by the score it earned, so it captures something token pricing misses: a reasoning model can emit many times more tokens than its per-token rate suggests. Claude Sonnet 5.5 works out at $0.0580 per point and Gemini 4 Hydrogen at $0.0192.

Does Claude Sonnet 5.5 or Gemini 4 Hydrogen have a bigger context window?

They are effectively the same — 1M for Claude Sonnet 5.5 and 1.0M for Gemini 4 Hydrogen.

Do Claude Sonnet 5.5 and Gemini 4 Hydrogen support prompt caching?

Both publish a cached-input rate: $0.100 per million for Claude Sonnet 5.5 and $0.075 for Gemini 4 Hydrogen, against full input rates of $2.00 and $1.50. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.

Related comparisons

How these numbers are produced

  • Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • Scores — LiveBench release 2026-11-06, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
  • “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.