Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. 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-5.6 Luna if you want a managed API.
GPT-5.6 Luna (OpenAI) and Llama 4 Maverick (Meta) are two of the models people most often weigh against each other in 2026. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. 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-5.6 Luna is API-metered at $1/$6 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-5.6 Luna is the newer model by about 15 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.6 Luna
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
July 9, 2026
April 2025
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$1/$6 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-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Open weights, 1M context: Llama 4 Maverick — A core design strength of Llama 4 Maverick.
Strong image + text understanding: Llama 4 Maverick — A core design strength of Llama 4 Maverick.
Self-hostable: Llama 4 Maverick — A core design strength of Llama 4 Maverick.
Lowest cost at scale: Llama 4 Maverick — At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: Llama 4 Maverick — At Open weight (self-host / free) it undercuts GPT-5.6 Luna, 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-5.6 Luna is API-only.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — It is specifically built for that.
Anyone whose priority is open weights, 1m context: Llama 4 Maverick — That is its strongest area.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs are real: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 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-5.6 Luna 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-5.6 Luna 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-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and 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-5.6 Luna 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-5.6 Luna is API-metered at $1/$6 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-5.6 Luna and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-5.6 Luna, 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-5.6 Luna or Llama 4 Maverick?
GPT-5.6 Luna — released July 9, 2026, about 15 months after Llama 4 Maverick.
GPT-5.6 Luna vs Llama 4 Maverick
OpenAI · US | Meta · US · Updated June 2026
Quick verdict
Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. 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-5.6 Luna if you want a managed API.
GPT-5.6 Luna (OpenAI) and Llama 4 Maverick (Meta) are two of the models people most often weigh against each other in 2026. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. 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-5.6 Luna is API-metered at $1/$6 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-5.6 Luna is the newer model by about 15 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.6 Luna
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
July 9, 2026
April 2025
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$1/$6 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-5.6 tier for high-volume drafting and automation
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Open weights, 1M context
Llama 4 Maverick
A core design strength of Llama 4 Maverick.
Strong image + text understanding
Llama 4 Maverick
A core design strength of Llama 4 Maverick.
Self-hostable
Llama 4 Maverick
A core design strength of Llama 4 Maverick.
Lowest cost at scale
Llama 4 Maverick
At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Llama 4 Maverick
At Open weight (self-host / free) it undercuts GPT-5.6 Luna, 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-5.6 Luna is API-only.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation
→ GPT-5.6 Luna
It is specifically built for that.
Anyone whose priority is open weights, 1m context
→ Llama 4 Maverick
That is its strongest area.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs are real: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 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-5.6 Luna 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-5.6 Luna 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-5.6 Luna 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-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and 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-5.6 Luna 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-5.6 Luna is API-metered at $1/$6 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-5.6 Luna and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-5.6 Luna, 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-5.6 Luna or Llama 4 Maverick?
GPT-5.6 Luna — released July 9, 2026, about 15 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.