// head_to_head

Nemotron 3 Ultra vs SpaceXAI: Grok Build 0.1

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 — Nemotron 3 Ultra is the cheaper way to get it.

The two are within 0.4 points overall, which is inside the range that effort settings alone move a LiveBench score, so treat them as quality-equivalent. Nemotron 3 Ultra lists 19% cheaper per blended million tokens. When quality ties, cost is the whole decision. The two cost measures disagree here, which is worth knowing: Nemotron 3 Ultra has the lower sticker price, but SpaceXAI: Grok Build 0.1 earns each point of capability for less — $0.0144 against $0.2118 — because per-token rates do not predict how many tokens a model actually spends on a task.

nvidia

Nemotron 3 Ultra

Blended / 1M
$1.05
Context
262K
Released
Jun 4, 2026
Overall score
67.4
reasoningtool callingprompt caching

x-ai

SpaceXAI: Grok Build 0.1

Blended / 1M
$1.25
Context
256K
Released
May 20, 2026
Overall score
67.8
reasoningtool callingimage inputfile inputprompt caching

Specs and pricing

MetricNemotron 3 UltraSpaceXAI: Grok Build 0.1
LiveBench overall

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

67.467.8
Cost per point

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

$0.2118$0.0144win
Blended price / 1M

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

$1.05win$1.25
Input price / 1M$0.600win$1.00
Output price / 1M$2.40$2.00win
Cached input / 1M

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

$0.120win$0.200
Context window262K256K
Max output tokens183K230Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Nemotron 3 Ultra on top, SpaceXAI: Grok Build 0.1 below, both out of 100.

Agentic coding
38.7
45.8
Coding
70.7
65.4
Reasoning
74.7
76.4
Mathematics
88.7
78.4
Data analysis
54.5
70.8
Language
70.8
72.5
Instruction following
73.4
65.2

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.

WorkloadNemotron 3 UltraSpaceXAI: Grok Build 0.1
Support chatbot

1.2K in / 400 out × 200K requests

$301.44/mo$342.40/mo
RAG assistant

8K in / 600 out × 100K requests

$432.00/mo$600.00/mo
Coding agent

40K in / 4K out × 20K requests

$403.20/mo$512.00/mo
Document extraction

20K in / 1.5K out × 50K requests

$756.00/mo$1,110/mo
Bulk classification

500 in / 20 out × 5M requests

$1,500/mo$2,300/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

SpaceXAI: Grok Build 0.1

Lowest measured cost per point of capability at $0.0144 per point — the gap compounds with every request.

The workload is coding or agentic work

SpaceXAI: Grok Build 0.1

Leads on agentic coding — 45.8 against 38.7.

You are cost-constrained

Nemotron 3 Ultra

Cheaper on blended list price at $1.05 per million tokens.

Nemotron 3 Ultra vs SpaceXAI: Grok Build 0.1 FAQ

Which is better, Nemotron 3 Ultra or SpaceXAI: Grok Build 0.1?

Effectively the same quality — Nemotron 3 Ultra is the cheaper way to get it. The two are within 0.4 points overall, which is inside the range that effort settings alone move a LiveBench score, so treat them as quality-equivalent. Nemotron 3 Ultra lists 19% cheaper per blended million tokens. When quality ties, cost is the whole decision. The two cost measures disagree here, which is worth knowing: Nemotron 3 Ultra has the lower sticker price, but SpaceXAI: Grok Build 0.1 earns each point of capability for less — $0.0144 against $0.2118 — because per-token rates do not predict how many tokens a model actually spends on a task.

Is Nemotron 3 Ultra cheaper than SpaceXAI: Grok Build 0.1?

Nemotron 3 Ultra is cheaper. On a 3:1 input:output blend, Nemotron 3 Ultra lists at $1.05 per million tokens and SpaceXAI: Grok Build 0.1 at $1.25 — Nemotron 3 Ultra is 19% cheaper. Input and output are priced separately — Nemotron 3 Ultra charges $0.600 in and $2.40 out, SpaceXAI: Grok Build 0.1 charges $1.00 and $2.00 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Nemotron 3 Ultra vs SpaceXAI: Grok Build 0.1: which scores higher on benchmarks?

Nemotron 3 Ultra scores 67.4 and SpaceXAI: Grok Build 0.1 scores 67.8 overall on LiveBench, the 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, Nemotron 3 Ultra or SpaceXAI: Grok Build 0.1?

SpaceXAI: Grok Build 0.1. 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. Nemotron 3 Ultra works out at $0.2118 per point and SpaceXAI: Grok Build 0.1 at $0.0144.

Does Nemotron 3 Ultra or SpaceXAI: Grok Build 0.1 have a bigger context window?

They are effectively the same — 262K for Nemotron 3 Ultra and 256K for SpaceXAI: Grok Build 0.1.

Do Nemotron 3 Ultra and SpaceXAI: Grok Build 0.1 support prompt caching?

Both publish a cached-input rate: $0.120 per million for Nemotron 3 Ultra and $0.200 for SpaceXAI: Grok Build 0.1, against full input rates of $0.600 and $1.00. 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.
  • 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.