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 Llama 4 Maverick for open weights, 1m context or strong image + text understanding. Choose Llama 4 Maverick if you need self-hosting or data privacy; GPT-5.4 Nano if you want a managed API.
GPT-5.4 Nano (OpenAI) and Llama 4 Maverick (Meta) 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Llama 4 Maverick 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: Llama 4 Maverick holds 2.5× more — 1M (~1,500 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: GPT-5.4 Nano is the newer model by about 12 months (released March 17, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.4 Nano
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
March 17, 2026
April 2025
Context window
400K (~600 pages)
1M (~1,500 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, image, 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 — 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 — and it is the newer of the two.
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; Llama 4 Maverick 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; Llama 4 Maverick does not.
Open weights, 1M context: Llama 4 Maverick — Its 1M window holds about 2.5× more than GPT-5.4 Nano's 400K in a single prompt.
Strong image + text understanding: Llama 4 Maverick — GPT-5.4 Nano is comparatively weak here — image input only — no audio or video
Self-hostable: Llama 4 Maverick — Open weights make this possible at all — GPT-5.4 Nano is API-only, so it cannot leave the vendor's servers.
Lowest cost at scale: Llama 4 Maverick — 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: Llama 4 Maverick — Its 1M window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Llama 4 Maverick — 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: Llama 4 Maverick — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: Llama 4 Maverick — 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 open weights, 1m context: Llama 4 Maverick — 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.
Llama 4 Maverick: where it fits
Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.
Its trade-offs: needs serious hardware to self-host, and trails closed frontier on 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
The defining split here is open vs. closed. Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick leans toward open weights, 1m context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Nano or Llama 4 Maverick?
Llama 4 Maverick 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?
Llama 4 Maverick — 1M vs 400K, about 2.5× 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 Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, Llama 4 Maverick 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 Llama 4 Maverick?
GPT-5.4 Nano — released March 17, 2026, about 12 months after Llama 4 Maverick.
GPT-5.4 Nano vs Llama 4 Maverick
OpenAI · US | Meta · 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 Llama 4 Maverick for open weights, 1m context or strong image + text understanding. Choose Llama 4 Maverick if you need self-hosting or data privacy; GPT-5.4 Nano if you want a managed API.
GPT-5.4 Nano (OpenAI) and Llama 4 Maverick (Meta) 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. 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: Llama 4 Maverick 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: Llama 4 Maverick holds 2.5× more — 1M (~1,500 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: GPT-5.4 Nano is the newer model by about 12 months (released March 17, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.4 Nano
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
March 17, 2026
April 2025
Context window
400K (~600 pages)
1M (~1,500 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, image, 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
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 — and it is the newer of the two.
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; Llama 4 Maverick 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; Llama 4 Maverick does not.
Open weights, 1M context
Llama 4 Maverick
Its 1M window holds about 2.5× more than GPT-5.4 Nano's 400K in a single prompt.
Strong image + text understanding
Llama 4 Maverick
GPT-5.4 Nano is comparatively weak here — image input only — no audio or video
Self-hostable
Llama 4 Maverick
Open weights make this possible at all — GPT-5.4 Nano is API-only, so it cannot leave the vendor's servers.
Lowest cost at scale
Llama 4 Maverick
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
Llama 4 Maverick
Its 1M window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Llama 4 Maverick
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
→ Llama 4 Maverick
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Llama 4 Maverick
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 open weights, 1m context
→ Llama 4 Maverick
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.
Llama 4 Maverick: where it fits
Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.
Its trade-offs: needs serious hardware to self-host, and trails closed frontier on 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
The defining split here is open vs. closed. Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick leans toward open weights, 1m context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Nano or Llama 4 Maverick?
Llama 4 Maverick 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?
Llama 4 Maverick — 1M vs 400K, about 2.5× 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 Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, Llama 4 Maverick 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 Llama 4 Maverick?
GPT-5.4 Nano — released March 17, 2026, about 12 months after Llama 4 Maverick.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.