Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. 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. Choose IBM Granite 4.1 if you need self-hosting or data privacy; GPT-5.4 Nano if you want a managed API.
GPT-5.4 Nano (OpenAI) and IBM Granite 4.1 (IBM) are two of the models people most often weigh against each other in 2026. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. 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. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: IBM Granite 4.1 ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-5.4 Nano is API-metered at $0.2/$1.25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: IBM Granite 4.1 holds 1.3× more — 512K (~768 pages) vs 400K (~600 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 43 days (released April 29, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.4 Nano
IBM Granite 4.1
Provider
OpenAI (US)
IBM (US)
Released
March 17, 2026
April 29, 2026
Context window
400K (~600 pages)
512K (~768 pages)
Price (in/out)
$0.2/$1.25 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — IBM Granite 4.1 is comparatively weak here — not a frontier-intelligence competitor - built for efficient deployment, not top benchmark scores
Classification, extraction, ranking and sub-agent execution at scale: GPT-5.4 Nano — GPT-5.4 Nano lists classification, extraction, ranking and sub-agent execution at scale among its strengths; IBM Granite 4.1 does not.
A 400K context in the smallest, fastest GPT-5.4 variant: GPT-5.4 Nano — GPT-5.4 Nano lists a 400K context in the smallest, fastest GPT-5.4 variant among its strengths; IBM Granite 4.1 does not.
Enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed: IBM Granite 4.1 — Open weights make this possible at all — GPT-5.4 Nano is API-only, so it cannot leave the vendor's servers.
Efficient hybrid Mamba-2/transformer design - much lower memory and faster inference: IBM Granite 4.1 — Its 512K window holds about 1.3× more than GPT-5.4 Nano's 400K in a single prompt.
512K-token context on small, deployable dense models (3B/8B/30B): 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.
Lowest cost at scale: IBM Granite 4.1 — Its weights are open, so at volume you pay for your own hardware instead of GPT-5.4 Nano's $0.2/$1.25 per 1M tokens.
Largest single-prompt input: IBM Granite 4.1 — Its 512K window is about 1.3× larger than GPT-5.4 Nano's 400K, fitting roughly 768 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: IBM Granite 4.1 — At Open weight (self-host / free) it undercuts GPT-5.4 Nano, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: IBM Granite 4.1 — Larger 512K window fits more in one prompt.
A team with data-privacy or self-hosting needs: IBM Granite 4.1 — Open weights let you run it on your own hardware; GPT-5.4 Nano is API-only.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — It is specifically built for that.
Anyone whose priority is enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed: IBM Granite 4.1 — That is its strongest area.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs are real: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
The defining split here is open vs. closed. IBM Granite 4.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.4 Nano gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is GPT-5.4 Nano or IBM Granite 4.1 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, GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work while IBM Granite 4.1 leans toward enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Nano or IBM Granite 4.1?
IBM Granite 4.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 Nano is API-metered at $0.2/$1.25 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
IBM Granite 4.1 — 512K vs 400K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 Nano and IBM Granite 4.1 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, IBM Granite 4.1 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, GPT-5.4 Nano or IBM Granite 4.1?
IBM Granite 4.1 — released April 29, 2026, about 43 days after GPT-5.4 Nano.
GPT-5.4 Nano vs IBM Granite 4.1
OpenAI · US | IBM · US · Updated June 2026
Quick verdict
Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. 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. Choose IBM Granite 4.1 if you need self-hosting or data privacy; GPT-5.4 Nano if you want a managed API.
GPT-5.4 Nano (OpenAI) and IBM Granite 4.1 (IBM) are two of the models people most often weigh against each other in 2026. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. 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. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: IBM Granite 4.1 ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-5.4 Nano is API-metered at $0.2/$1.25 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: IBM Granite 4.1 holds 1.3× more — 512K (~768 pages) vs 400K (~600 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 43 days (released April 29, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.4 Nano
IBM Granite 4.1
Provider
OpenAI (US)
IBM (US)
Released
March 17, 2026
April 29, 2026
Context window
400K (~600 pages)
512K (~768 pages)
Price (in/out)
$0.2/$1.25 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
GPT-5.4 Nano
IBM Granite 4.1 is comparatively weak here — not a frontier-intelligence competitor - built for efficient deployment, not top benchmark scores
Classification, extraction, ranking and sub-agent execution at scale
GPT-5.4 Nano
GPT-5.4 Nano lists classification, extraction, ranking and sub-agent execution at scale among its strengths; IBM Granite 4.1 does not.
A 400K context in the smallest, fastest GPT-5.4 variant
GPT-5.4 Nano
GPT-5.4 Nano lists a 400K context in the smallest, fastest GPT-5.4 variant among its strengths; IBM Granite 4.1 does not.
Enterprise-grade open weights - Apache 2.0, ISO 42001-certified, cryptographically signed
IBM Granite 4.1
Open weights make this possible at all — GPT-5.4 Nano is API-only, so it cannot leave the vendor's servers.
Efficient hybrid Mamba-2/transformer design - much lower memory and faster inference
IBM Granite 4.1
Its 512K window holds about 1.3× more than GPT-5.4 Nano's 400K in a single prompt.
512K-token context on small, deployable dense models (3B/8B/30B)
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.
Lowest cost at scale
IBM Granite 4.1
Its weights are open, so at volume you pay for your own hardware instead of GPT-5.4 Nano's $0.2/$1.25 per 1M tokens.
Largest single-prompt input
IBM Granite 4.1
Its 512K window is about 1.3× larger than GPT-5.4 Nano's 400K, fitting roughly 768 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ IBM Granite 4.1
At Open weight (self-host / free) it undercuts GPT-5.4 Nano, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ IBM Granite 4.1
Larger 512K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ IBM Granite 4.1
Open weights let you run it on your own hardware; GPT-5.4 Nano is API-only.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
→ GPT-5.4 Nano
It is specifically built for that.
Anyone whose priority is enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed
→ IBM Granite 4.1
That is its strongest area.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs are real: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
The defining split here is open vs. closed. IBM Granite 4.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.4 Nano gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GPT-5.4 Nano and IBM Granite 4.1 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 GPT-5.4 Nano or IBM Granite 4.1 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, GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work while IBM Granite 4.1 leans toward enterprise-grade open weights - apache 2.0, iso 42001-certified, cryptographically signed, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Nano or IBM Granite 4.1?
IBM Granite 4.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 Nano is API-metered at $0.2/$1.25 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
IBM Granite 4.1 — 512K vs 400K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 Nano and IBM Granite 4.1 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, IBM Granite 4.1 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, GPT-5.4 Nano or IBM Granite 4.1?
IBM Granite 4.1 — released April 29, 2026, about 43 days after GPT-5.4 Nano.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.