Pick GPT-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. 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-5.5 if you want a managed API.
GPT-5.5 (OpenAI) and Llama 4 Maverick (Meta) are two of the models people most often weigh against each other in 2026. GPT-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. They diverge most on price 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-5.5 is API-metered at $5/$30 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: GPT-5.5 is the newer model by about 13 months (released April 23, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.5
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
April 23, 2026
April 2025
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$5/$30 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
Terminal, CLI and computer-use automation: GPT-5.5 — OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion — and it is the newer of the two.
Long-horizon tool sequencing: GPT-5.5 — GPT-5.5 lists long-horizon tool sequencing among its strengths; Llama 4 Maverick does not.
Strong agentic coding and reasoning: GPT-5.5 — Llama 4 Maverick is comparatively weak here — trails closed frontier on reasoning
Open weights, 1M context: Llama 4 Maverick — Open weights make this possible at all — GPT-5.5 is API-only, so it cannot leave the vendor's servers.
Strong image + text understanding: Llama 4 Maverick — Meta's open-weight 1M-context multimodal model for self-hosted deployments — and its weights are open while GPT-5.5 is API-only.
Self-hostable: Llama 4 Maverick — Llama 4 Maverick lists self-hostable among its strengths; GPT-5.5 does not.
Lowest cost at scale: Llama 4 Maverick — Its weights are open, so at volume you pay for your own hardware instead of GPT-5.5's $5/$30 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Llama 4 Maverick — At Open weight (self-host / free) it undercuts GPT-5.5, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: Llama 4 Maverick — Open weights let you run it on your own hardware; GPT-5.5 is API-only.
Anyone whose priority is terminal, cli and computer-use automation: GPT-5.5 — It is specifically built for that.
Anyone whose priority is open weights, 1m context: Llama 4 Maverick — That is its strongest area.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs are real: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium 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-5.5 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-5.5 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-5.5 leans toward terminal, cli and computer-use automation 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-5.5 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-5.5 is API-metered at $5/$30 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-5.5 and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-5.5, 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-5.5 or Llama 4 Maverick?
GPT-5.5 — released April 23, 2026, about 13 months after Llama 4 Maverick.
GPT-5.5 vs Llama 4 Maverick
OpenAI · US | Meta · US · Updated June 2026
Quick verdict
Pick GPT-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. 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-5.5 if you want a managed API.
GPT-5.5 (OpenAI) and Llama 4 Maverick (Meta) are two of the models people most often weigh against each other in 2026. GPT-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. They diverge most on price 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-5.5 is API-metered at $5/$30 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-5.5 is the newer model by about 13 months (released April 23, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.5
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
April 23, 2026
April 2025
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$5/$30 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
Terminal, CLI and computer-use automation
GPT-5.5
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion — and it is the newer of the two.
Long-horizon tool sequencing
GPT-5.5
GPT-5.5 lists long-horizon tool sequencing among its strengths; Llama 4 Maverick does not.
Strong agentic coding and reasoning
GPT-5.5
Llama 4 Maverick is comparatively weak here — trails closed frontier on reasoning
Open weights, 1M context
Llama 4 Maverick
Open weights make this possible at all — GPT-5.5 is API-only, so it cannot leave the vendor's servers.
Strong image + text understanding
Llama 4 Maverick
Meta's open-weight 1M-context multimodal model for self-hosted deployments — and its weights are open while GPT-5.5 is API-only.
Self-hostable
Llama 4 Maverick
Llama 4 Maverick lists self-hostable among its strengths; GPT-5.5 does not.
Lowest cost at scale
Llama 4 Maverick
Its weights are open, so at volume you pay for your own hardware instead of GPT-5.5's $5/$30 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Llama 4 Maverick
At Open weight (self-host / free) it undercuts GPT-5.5, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ Llama 4 Maverick
Open weights let you run it on your own hardware; GPT-5.5 is API-only.
Anyone whose priority is terminal, cli and computer-use automation
→ GPT-5.5
It is specifically built for that.
Anyone whose priority is open weights, 1m context
→ Llama 4 Maverick
That is its strongest area.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs are real: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium 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-5.5 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-5.5 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.
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-5.5 leans toward terminal, cli and computer-use automation 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-5.5 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-5.5 is API-metered at $5/$30 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-5.5 and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-5.5, 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-5.5 or Llama 4 Maverick?
GPT-5.5 — released April 23, 2026, about 13 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.