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Gemini 3.7 Flash vs Hermes 4 405B

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

Gemini 3.7 Flash and Hermes 4 405B are priced within ~10% of each other.

Hermes 4 405B 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

Gemini 3.7 Flash

Blended / 1M
$1.50
Context
1.0M
Released
Aug 13, 2026
Overall score
78.8
reasoningtool callingimage inputvideo inputfile inputaudio inputprompt caching

nousresearch

Hermes 4 405B

Blended / 1M
$1.50
Context
131K
Released
Aug 26, 2025
Overall score
Not evaluated
reasoning

Specs and pricing

MetricGemini 3.7 FlashHermes 4 405B
LiveBench overall

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

78.8
Cost per point

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

$0.0875
Blended price / 1M

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

$1.50$1.50
Input price / 1M$0.750win$1.00
Output price / 1M$3.75$3.00win
Cached input / 1M

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

$0.075
Context window1.0Mwin131K
Max output tokens66K118Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Gemini 3.7 Flash on top, Hermes 4 405B below, both out of 100.

Agentic coding
58.3
Coding
78.9
Reasoning
87.8
Mathematics
93.5
Data analysis
68.0
Language
85.5
Instruction following
79.9

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.

WorkloadGemini 3.7 FlashHermes 4 405B
Support chatbot

1.2K in / 400 out × 200K requests

$431.40/mo$480.00/mo
RAG assistant

8K in / 600 out × 100K requests

$555.00/mo$980.00/mo
Coding agent

40K in / 4K out × 20K requests

$522.00/mo$1,040/mo
Document extraction

20K in / 1.5K out × 50K requests

$997.50/mo$1,225/mo
Bulk classification

500 in / 20 out × 5M requests

$1,912/mo$2,800/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

Gemini 3.7 Flash

Wider context window — 1.0M against 131K.

Gemini 3.7 Flash vs Hermes 4 405B FAQ

Which is better, Gemini 3.7 Flash or Hermes 4 405B?

Gemini 3.7 Flash and Hermes 4 405B are priced within ~10% of each other. Hermes 4 405B 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 3.7 Flash cheaper than Hermes 4 405B?

They cost about the same. Both land near $1.50 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

Does Gemini 3.7 Flash or Hermes 4 405B have a bigger context window?

Gemini 3.7 Flash has the larger context window: 1.0M for Gemini 3.7 Flash against 131K for Hermes 4 405B. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.

Do Gemini 3.7 Flash and Hermes 4 405B support prompt caching?

Gemini 3.7 Flash publishes a cached-input rate of $0.075 per million tokens against a full input rate of $0.750. The catalogue lists no separate cached rate for Hermes 4 405B, 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.
  • ScoresLiveBench release 2026-06-25, 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.