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 Llama 4 Scout for largest advertised context (10m) or open weights, single-gpu friendly.
IBM Granite 4.1 (IBM) and Llama 4 Scout (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. Llama 4 Scout is the 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: Llama 4 Scout holds 20× more — 10M (~15,000 pages) vs 512K (~768 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: IBM Granite 4.1 is the newer model by about 13 months (released April 29, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
IBM Granite 4.1
Llama 4 Scout
Provider
IBM (US)
Meta (US)
Released
April 29, 2026
April 2025
Context window
512K (~768 pages)
10M (~15,000 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
15%
Who wins what
Enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed: IBM Granite 4.1 — Llama 4 Scout is comparatively weak here — effective recall degrades far below 10M
Efficient hybrid Mamba-2/transformer design - much lower memory and faster inference: 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 is the newer of the two.
512K-token context on small, deployable dense models (3B/8B/30B): IBM Granite 4.1 — Llama 4 Scout is comparatively weak here — ~15% on long-context multi-needle reasoning
Largest advertised context (10M): Llama 4 Scout — Its 10M window holds about 20× more than IBM Granite 4.1's 512K in a single prompt.
Open weights, single-GPU friendly: Llama 4 Scout — The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller — and it carries the larger 10M context.
Self-hosted, data-private deployment: Llama 4 Scout — IBM Granite 4.1 is comparatively weak here — not a frontier-intelligence competitor - built for efficient deployment, not top benchmark scores
Largest single-prompt input: Llama 4 Scout — Its 10M window is about 20× larger than IBM Granite 4.1's 512K, fitting roughly 15,000 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases: Llama 4 Scout — Larger 10M 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 largest advertised context (10m): Llama 4 Scout — 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.
Llama 4 Scout: where it fits
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Released April 2025 by Meta, it is built for largest advertised context (10M), open weights, single-GPU friendly, self-hosted, data-private deployment, and retrieval over very long inputs.
Its trade-offs: effective recall degrades far below 10M, and ~15% on long-context multi-needle reasoning. 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 Llama 4 Scout overlap enough that the right pick depends on your specific job. Llama 4 Scout 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, Llama 4 Scout for largest advertised context (10m). 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 Llama 4 Scout 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 Llama 4 Scout leans toward largest advertised context (10m), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, IBM Granite 4.1 or Llama 4 Scout?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Llama 4 Scout — 10M vs 512K, about 20× 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 Llama 4 Scout together?
Yes — a multi-model platform like LumiChats gives you IBM Granite 4.1, Llama 4 Scout 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 Llama 4 Scout?
IBM Granite 4.1 — released April 29, 2026, about 13 months after Llama 4 Scout.
IBM Granite 4.1 vs Llama 4 Scout
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 Llama 4 Scout for largest advertised context (10m) or open weights, single-gpu friendly.
IBM Granite 4.1 (IBM) and Llama 4 Scout (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. Llama 4 Scout is the 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. 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: Llama 4 Scout holds 20× more — 10M (~15,000 pages) vs 512K (~768 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: IBM Granite 4.1 is the newer model by about 13 months (released April 29, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
IBM Granite 4.1
Llama 4 Scout
Provider
IBM (US)
Meta (US)
Released
April 29, 2026
April 2025
Context window
512K (~768 pages)
10M (~15,000 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
15%
Who wins what
Enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed
IBM Granite 4.1
Llama 4 Scout is comparatively weak here — effective recall degrades far below 10M
Efficient hybrid Mamba-2/transformer design - much lower memory and faster inference
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 is the newer of the two.
512K-token context on small, deployable dense models (3B/8B/30B)
IBM Granite 4.1
Llama 4 Scout is comparatively weak here — ~15% on long-context multi-needle reasoning
Largest advertised context (10M)
Llama 4 Scout
Its 10M window holds about 20× more than IBM Granite 4.1's 512K in a single prompt.
Open weights, single-GPU friendly
Llama 4 Scout
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller — and it carries the larger 10M context.
Self-hosted, data-private deployment
Llama 4 Scout
IBM Granite 4.1 is comparatively weak here — not a frontier-intelligence competitor - built for efficient deployment, not top benchmark scores
Largest single-prompt input
Llama 4 Scout
Its 10M window is about 20× larger than IBM Granite 4.1's 512K, fitting roughly 15,000 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Llama 4 Scout
Larger 10M 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 largest advertised context (10m)
→ Llama 4 Scout
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.
Llama 4 Scout: where it fits
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Released April 2025 by Meta, it is built for largest advertised context (10M), open weights, single-GPU friendly, self-hosted, data-private deployment, and retrieval over very long inputs.
Its trade-offs: effective recall degrades far below 10M, and ~15% on long-context multi-needle reasoning. 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 Llama 4 Scout overlap enough that the right pick depends on your specific job. Llama 4 Scout 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, Llama 4 Scout for largest advertised context (10m). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both IBM Granite 4.1 and Llama 4 Scout 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 Llama 4 Scout 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 Llama 4 Scout leans toward largest advertised context (10m), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, IBM Granite 4.1 or Llama 4 Scout?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Llama 4 Scout — 10M vs 512K, about 20× 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 Llama 4 Scout together?
Yes — a multi-model platform like LumiChats gives you IBM Granite 4.1, Llama 4 Scout 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 Llama 4 Scout?
IBM Granite 4.1 — released April 29, 2026, about 13 months after Llama 4 Scout.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.