Muse Glimmer vs NVIDIA Nemotron 3 Super

Meta · US  |  NVIDIA · US · Updated June 2026

Quick verdict

Pick Muse Glimmer for runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit or open weights (apache 2.0), free to self-host and offline-capable - data never leaves your machine. Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m).

Muse Glimmer (Meta) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Muse Glimmer is meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.

Key differences at a glance

Side-by-side specs

SpecMuse GlimmerNVIDIA Nemotron 3 Super
ProviderMeta (US) NVIDIA (US)
ReleasedAugust 10, 2026 March 11, 2026
Context window128K (~197 pages) 1M (~1,500 pages)
Price (in/out)Open weight (self-host / free) Open weight (self-host / free)
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, image, code text, code
SWE-Bench VerifiedNot published 60.47%
MRCR v2 @ 1MNot published Not published

Who wins what

Runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit

Muse Glimmer

Meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models — and it is the newer of the two.

Open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine

Muse Glimmer

Muse Glimmer lists open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine among its strengths; NVIDIA Nemotron 3 Super does not.

Agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery

Muse Glimmer

Muse Glimmer lists agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery among its strengths; NVIDIA Nemotron 3 Super does not.

High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)

NVIDIA Nemotron 3 Super

NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context — and it carries the larger 1M context.

1M-token context with strong long-context retrieval (91.6% RULER @ 1M)

NVIDIA Nemotron 3 Super

Its 1M window holds about 7.6× more than Muse Glimmer's 128K in a single prompt.

Strong math reasoning (90.21% AIME 2025)

NVIDIA Nemotron 3 Super

NVIDIA Nemotron 3 Super lists strong math reasoning (90.21% AIME 2025) among its strengths; Muse Glimmer does not.

Largest single-prompt input

NVIDIA Nemotron 3 Super

Its 1M window is about 7.6× larger than Muse Glimmer's 128K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

Someone analysing very long documents or codebases

NVIDIA Nemotron 3 Super

Larger 1M window fits more in one prompt.

Anyone whose priority is runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit

Muse Glimmer

It is specifically built for that.

Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b)

NVIDIA Nemotron 3 Super

That is its strongest area.

Muse Glimmer: where it fits

Meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. Released August 10, 2026 by Meta, it is built for runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit, open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine, agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery, and 128K context, text and image input, trained on 100+ languages.

Its trade-offs are real: a distilled ~30B model - ceiling below its closed teacher (Muse Spark) and cloud flagships, no independent Artificial Analysis intelligence score published yet, published benchmarks (e.g. SWE-Bench Verified 76.0) are Meta's own, and 4-bit quantization to fit consumer GPUs trades away some accuracy. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

NVIDIA Nemotron 3 Super: where it fits

NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.

Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

Muse Glimmer and NVIDIA Nemotron 3 Super overlap enough that the right pick depends on your specific job. NVIDIA Nemotron 3 Super holds the larger context; and each leads in its own area — Muse Glimmer for runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit, NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b). Rather than crowning one, run the same hard task through both once and let the results decide.

Want both Muse Glimmer and NVIDIA Nemotron 3 Super without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is Muse Glimmer or NVIDIA Nemotron 3 Super better for coding?

Public SWE-Bench figures are not available for Muse Glimmer, so the honest test is your own repository — run an identical real bug through both. By design, Muse Glimmer leans toward runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Muse Glimmer or NVIDIA Nemotron 3 Super?

They are priced almost identically, so cost will not decide between them.

Which has the bigger context window?

NVIDIA Nemotron 3 Super — 1M vs 128K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Muse Glimmer and NVIDIA Nemotron 3 Super together?

Yes — a multi-model platform like LumiChats gives you Muse Glimmer, NVIDIA Nemotron 3 Super and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, Muse Glimmer or NVIDIA Nemotron 3 Super?

Muse Glimmer — released August 10, 2026, about 5 months after NVIDIA Nemotron 3 Super.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.