// head_to_head
Gemini 4 Hydrogen vs Ling 3.2 Flash (free)
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.
Ling 3.2 Flash (free) is the cheaper of the two; neither can be ranked on quality here.
Ling 3.2 Flash (free) does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
Gemini 4 Hydrogen
- Blended / 1M
- $3.00
- Context
- 1.0M
- Released
- Nov 12, 2026
- Overall score
- 77.0
inclusionai
Ling 3.2 Flash (free)
- Blended / 1M
- Free
- Context
- 1.0M
- Released
- Nov 13, 2026
- Overall score
- Not evaluated
Specs and pricing
| Metric | Gemini 4 Hydrogen | Ling 3.2 Flash (free) |
|---|---|---|
| LiveBench overall Weighted mean of the seven LiveBench category scores, 0–100. Higher is better. | 77.0 | — |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.0192 | — |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $3.00 | Freewin |
| Input price / 1M | $1.50 | Freewin |
| Output price / 1M | $7.50 | Freewin |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.075 | — |
| Context window | 1.0M | 1.0M |
| Max output tokens | 944Kwin | 262K |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Gemini 4 Hydrogen on top, Ling 3.2 Flash (free) below, both out of 100.
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.
| Workload | Gemini 4 Hydrogen | Ling 3.2 Flash (free) |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $857.40/mo | $0/mo |
| RAG assistant 8K in / 600 out × 100K requests | $1,080/mo | $0/mo |
| Coding agent 40K in / 4K out × 20K requests | $1,002/mo | $0/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $1,991/mo | $0/mo |
| Bulk classification 500 in / 20 out × 5M requests | $3,787/mo | $0/mo |
Which should you pick?
You are cost-constrained
Ling 3.2 Flash (free)
Cheaper on blended list price at Free per million tokens.
Gemini 4 Hydrogen vs Ling 3.2 Flash (free) FAQ
Which is better, Gemini 4 Hydrogen or Ling 3.2 Flash (free)?
Ling 3.2 Flash (free) is the cheaper of the two; neither can be ranked on quality here. Ling 3.2 Flash (free) does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
Is Gemini 4 Hydrogen cheaper than Ling 3.2 Flash (free)?
Ling 3.2 Flash (free) is cheaper. On a 3:1 input:output blend, Gemini 4 Hydrogen lists at $3.00 per million tokens and Ling 3.2 Flash (free) at Free. Input and output are priced separately — Gemini 4 Hydrogen charges $1.50 in and $7.50 out, Ling 3.2 Flash (free) charges Free and Free — so the model that looks cheaper flips depending on how output-heavy your workload is.
Does Gemini 4 Hydrogen or Ling 3.2 Flash (free) have a bigger context window?
They are effectively the same — 1.0M for Gemini 4 Hydrogen and 1.0M for Ling 3.2 Flash (free).
Do Gemini 4 Hydrogen and Ling 3.2 Flash (free) support prompt caching?
Gemini 4 Hydrogen publishes a cached-input rate of $0.075 per million tokens against a full input rate of $1.50. The catalogue lists no separate cached rate for Ling 3.2 Flash (free), which means the provider does not price it separately here — not that caching is unavailable.
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.