Pick IBM Granite 4.1 for enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed or efficient hybrid mamba-2/transformer design - much lower memory and faster inference. 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.
IBM Granite 4.1 (IBM) and Muse Glimmer (Meta) are two of the models people most often weigh against each other in 2026. IBM Granite 4.1 is iBM's most complete open-weight enterprise release - small, Apache-2.0, long-context and governance-friendly, built to deploy efficiently rather than top the leaderboard. 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. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: IBM Granite 4.1 holds 3.9× more — 512K (~768 pages) vs 128K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Muse Glimmer is the newer model by about 3 months (released August 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
IBM Granite 4.1
Muse Glimmer
Provider
IBM (US)
Meta (US)
Released
April 29, 2026
August 10, 2026
Context window
512K (~768 pages)
128K (~197 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed: IBM Granite 4.1 — IBM's most complete open-weight enterprise release - small, Apache-2.0, long-context and governance-friendly, built to deploy efficiently rather than top the leaderboard — and it carries the larger 512K context.
Efficient hybrid Mamba-2/transformer design - much lower memory and faster inference: IBM Granite 4.1 — Its 512K window holds about 3.9× more than Muse Glimmer's 128K in a single prompt.
512K-token context on small, deployable dense models (3B/8B/30B): IBM Granite 4.1 — IBM Granite 4.1 lists 512K-token context on small, deployable dense models (3B/8B/30B) among its strengths; Muse Glimmer does not.
Runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit: Muse Glimmer — IBM Granite 4.1 is comparatively weak here — best as a workhorse; reasoning-heavy tasks favor larger models
Open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine: 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.
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; IBM Granite 4.1 does not.
Largest single-prompt input: IBM Granite 4.1 — Its 512K window is about 3.9× larger than Muse Glimmer's 128K, fitting roughly 768 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases: IBM Granite 4.1 — Larger 512K window fits more in one prompt.
Anyone whose priority is enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed: IBM Granite 4.1 — It is specifically built for that.
Anyone whose priority is runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit: Muse Glimmer — That is its strongest area.
IBM Granite 4.1: where it fits
IBM's most complete open-weight enterprise release - small, Apache-2.0, long-context and governance-friendly, built to deploy efficiently rather than top the leaderboard. Released April 29, 2026 by IBM, it is built for enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed, efficient hybrid Mamba-2/transformer design - much lower memory and faster inference, 512K-token context on small, deployable dense models (3B/8B/30B), and free to self-host; governance-friendly for on-prem and regulated deployments.
Its trade-offs are real: not a frontier-intelligence competitor - built for efficient deployment, not top benchmark scores, best as a workhorse; reasoning-heavy tasks favor larger models, instruct models are text-focused (vision and speech are separate family members), and efficiency and performance claims are IBM's own. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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: 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.
The bottom line for this matchup
IBM Granite 4.1 and Muse Glimmer overlap enough that the right pick depends on your specific job. IBM Granite 4.1 holds the larger context; and each leads in its own area — IBM Granite 4.1 for enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed, Muse Glimmer for runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is IBM Granite 4.1 or Muse Glimmer better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, IBM Granite 4.1 leans toward enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed while Muse Glimmer leans toward runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, IBM Granite 4.1 or Muse Glimmer?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
IBM Granite 4.1 — 512K vs 128K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both IBM Granite 4.1 and Muse Glimmer together?
Yes — a multi-model platform like LumiChats gives you IBM Granite 4.1, Muse Glimmer 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, IBM Granite 4.1 or Muse Glimmer?
Muse Glimmer — released August 10, 2026, about 3 months after IBM Granite 4.1.
IBM Granite 4.1 vs Muse Glimmer
IBM · US | Meta · US · Updated June 2026
Quick verdict
Pick IBM Granite 4.1 for enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed or efficient hybrid mamba-2/transformer design - much lower memory and faster inference. 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.
IBM Granite 4.1 (IBM) and Muse Glimmer (Meta) are two of the models people most often weigh against each other in 2026. IBM Granite 4.1 is iBM's most complete open-weight enterprise release - small, Apache-2.0, long-context and governance-friendly, built to deploy efficiently rather than top the leaderboard. 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. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: IBM Granite 4.1 holds 3.9× more — 512K (~768 pages) vs 128K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Muse Glimmer is the newer model by about 3 months (released August 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
IBM Granite 4.1
Muse Glimmer
Provider
IBM (US)
Meta (US)
Released
April 29, 2026
August 10, 2026
Context window
512K (~768 pages)
128K (~197 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed
IBM Granite 4.1
IBM's most complete open-weight enterprise release - small, Apache-2.0, long-context and governance-friendly, built to deploy efficiently rather than top the leaderboard — and it carries the larger 512K context.
Efficient hybrid Mamba-2/transformer design - much lower memory and faster inference
IBM Granite 4.1
Its 512K window holds about 3.9× more than Muse Glimmer's 128K in a single prompt.
512K-token context on small, deployable dense models (3B/8B/30B)
IBM Granite 4.1
IBM Granite 4.1 lists 512K-token context on small, deployable dense models (3B/8B/30B) among its strengths; Muse Glimmer does not.
Runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit
Muse Glimmer
IBM Granite 4.1 is comparatively weak here — best as a workhorse; reasoning-heavy tasks favor larger models
Open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine
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.
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; IBM Granite 4.1 does not.
Largest single-prompt input
IBM Granite 4.1
Its 512K window is about 3.9× larger than Muse Glimmer's 128K, fitting roughly 768 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ IBM Granite 4.1
Larger 512K window fits more in one prompt.
Anyone whose priority is enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed
→ IBM Granite 4.1
It is specifically built for that.
Anyone whose priority is runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit
→ Muse Glimmer
That is its strongest area.
IBM Granite 4.1: where it fits
IBM's most complete open-weight enterprise release - small, Apache-2.0, long-context and governance-friendly, built to deploy efficiently rather than top the leaderboard. Released April 29, 2026 by IBM, it is built for enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed, efficient hybrid Mamba-2/transformer design - much lower memory and faster inference, 512K-token context on small, deployable dense models (3B/8B/30B), and free to self-host; governance-friendly for on-prem and regulated deployments.
Its trade-offs are real: not a frontier-intelligence competitor - built for efficient deployment, not top benchmark scores, best as a workhorse; reasoning-heavy tasks favor larger models, instruct models are text-focused (vision and speech are separate family members), and efficiency and performance claims are IBM's own. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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: 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.
The bottom line for this matchup
IBM Granite 4.1 and Muse Glimmer overlap enough that the right pick depends on your specific job. IBM Granite 4.1 holds the larger context; and each leads in its own area — IBM Granite 4.1 for enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed, Muse Glimmer for runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both IBM Granite 4.1 and Muse Glimmer 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.
Is IBM Granite 4.1 or Muse Glimmer better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, IBM Granite 4.1 leans toward enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed while Muse Glimmer leans toward runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, IBM Granite 4.1 or Muse Glimmer?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
IBM Granite 4.1 — 512K vs 128K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both IBM Granite 4.1 and Muse Glimmer together?
Yes — a multi-model platform like LumiChats gives you IBM Granite 4.1, Muse Glimmer 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, IBM Granite 4.1 or Muse Glimmer?
Muse Glimmer — released August 10, 2026, about 3 months after IBM Granite 4.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.