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Hermes 4 405B vs SpaceXAI: Grok 4.3

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

Hermes 4 405B and SpaceXAI: Grok 4.3 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.

nousresearch

Hermes 4 405B

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

x-ai

SpaceXAI: Grok 4.3

Blended / 1M
$1.56
Context
1M
Released
Apr 30, 2026
Overall score
62.2
reasoningtool callingimage inputfile inputprompt caching

Specs and pricing

MetricHermes 4 405BSpaceXAI: Grok 4.3
LiveBench overall

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

62.2
Cost per point

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

$0.0325
Blended price / 1M

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

$1.50$1.56
Input price / 1M$1.00win$1.25
Output price / 1M$3.00$2.50win
Cached input / 1M

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

$0.200
Context window131K1Mwin
Max output tokens118K900Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Hermes 4 405B on top, SpaceXAI: Grok 4.3 below, both out of 100.

Agentic coding
18.5
Coding
69.9
Reasoning
70.8
Mathematics
84.3
Data analysis
55.8
Language
73.6
Instruction following
62.8

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.

WorkloadHermes 4 405BSpaceXAI: Grok 4.3
Support chatbot

1.2K in / 400 out × 200K requests

$480.00/mo$424.40/mo
RAG assistant

8K in / 600 out × 100K requests

$980.00/mo$730.00/mo
Coding agent

40K in / 4K out × 20K requests

$1,040/mo$612.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$1,225/mo$1,385/mo
Bulk classification

500 in / 20 out × 5M requests

$2,800/mo$2,850/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

SpaceXAI: Grok 4.3

Wider context window — 1M against 131K.

Hermes 4 405B vs SpaceXAI: Grok 4.3 FAQ

Which is better, Hermes 4 405B or SpaceXAI: Grok 4.3?

Hermes 4 405B and SpaceXAI: Grok 4.3 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 Hermes 4 405B cheaper than SpaceXAI: Grok 4.3?

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 Hermes 4 405B or SpaceXAI: Grok 4.3 have a bigger context window?

SpaceXAI: Grok 4.3 has the larger context window: 131K for Hermes 4 405B against 1M for SpaceXAI: Grok 4.3. 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 Hermes 4 405B and SpaceXAI: Grok 4.3 support prompt caching?

SpaceXAI: Grok 4.3 publishes a cached-input rate of $0.200 per million tokens against a full input rate of $1.25. 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.