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Gemma 4 31B vs Hy3

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

Gemma 4 31B and Hy3 are priced within ~10% of each other.

Hy3 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.

google

Gemma 4 31B

Blended / 1M
$0.250
Context
262K
Released
Apr 2, 2026
Overall score
38.7
reasoningtool callingimage inputvideo input

tencent

Hy3

Blended / 1M
$0.231
Context
262K
Released
Jul 6, 2026
Overall score
Not evaluated
reasoningtool callingprompt caching

Specs and pricing

MetricGemma 4 31BHy3
LiveBench overall

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

38.7—
Cost per point

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

$0.0017—
Blended price / 1M

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

$0.250$0.231
Input price / 1M$0.200$0.132win
Output price / 1M$0.400win$0.528
Cached input / 1M

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

—$0.033
Context window262K262K
Max output tokens16K128Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Gemma 4 31B on top, Hy3 below, both out of 100.

Long-horizon agentic
10.7
—
Coding
49.0
—
Reasoning
68.3
—
Browser
0.0
—
Data analysis
53.3
—
Research
44.4
—
Documents & design
58.4
—

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.

WorkloadGemma 4 31BHy3
Support chatbot

1.2K in / 400 out × 200K requests

$80.00/mo$66.79/mo
RAG assistant

8K in / 600 out × 100K requests

$184.00/mo$97.68/mo
Coding agent

40K in / 4K out × 20K requests

$192.00/mo$92.40/mo
Document extraction

20K in / 1.5K out × 50K requests

$230.00/mo$166.65/mo
Bulk classification

500 in / 20 out × 5M requests

$540.00/mo$333.30/mo
Run these two through the cost calculator

Gemma 4 31B vs Hy3 FAQ

Which is better, Gemma 4 31B or Hy3?

Gemma 4 31B and Hy3 are priced within ~10% of each other. Hy3 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 Gemma 4 31B cheaper than Hy3?

They cost about the same. Both land near $0.250 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

Does Gemma 4 31B or Hy3 have a bigger context window?

They are effectively the same — 262K for Gemma 4 31B and 262K for Hy3.

Do Gemma 4 31B and Hy3 support prompt caching?

Hy3 publishes a cached-input rate of $0.033 per million tokens against a full input rate of $0.132. The catalogue lists no separate cached rate for Gemma 4 31B, 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 2026-10-25, 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.