Pick GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment or openai says it makes about half as many mistakes as gpt-5.6 sol. 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-6 Sol if you want a managed API.
GPT-6 Sol (OpenAI) and Llama 4 Maverick (Meta) are two of the models people most often weigh against each other in 2026. GPT-6 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. 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-6 Sol is API-metered at $2/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 1.05M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: GPT-6 Sol is the newer model by about 18 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-6 Sol
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
September 22, 2026
April 2025
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$2/$10 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol: GPT-6 Sol — GPT-6 Sol lists openAI says it makes about half as many mistakes as GPT-5.6 Sol among its strengths; Llama 4 Maverick does not.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30): GPT-6 Sol — GPT-6 Sol lists priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30) among its strengths; Llama 4 Maverick does not.
Open weights, 1M context: Llama 4 Maverick — Open weights make this possible at all — GPT-6 Sol 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-6 Sol is API-only.
Self-hostable: Llama 4 Maverick — Llama 4 Maverick lists self-hostable among its strengths; GPT-6 Sol 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-6 Sol's $2/$10 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-6 Sol, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Sol — Larger 1.05M tokens 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-6 Sol is API-only.
Anyone whose priority is openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — It is specifically built for that.
Anyone whose priority is open weights, 1m context: Llama 4 Maverick — That is its strongest area.
GPT-6 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs are real: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid 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-6 Sol 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-6 Sol 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-6 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment 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-6 Sol 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-6 Sol is API-metered at $2/$10 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?
Effectively neither — 1.05M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-6 Sol and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Sol, 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-6 Sol or Llama 4 Maverick?
GPT-6 Sol — released September 22, 2026, about 18 months after Llama 4 Maverick.
GPT-6 Sol vs Llama 4 Maverick
OpenAI · US | Meta · US · Updated June 2026
Quick verdict
Pick GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment or openai says it makes about half as many mistakes as gpt-5.6 sol. 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-6 Sol if you want a managed API.
GPT-6 Sol (OpenAI) and Llama 4 Maverick (Meta) are two of the models people most often weigh against each other in 2026. GPT-6 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. 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-6 Sol is API-metered at $2/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 1.05M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-6 Sol is the newer model by about 18 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-6 Sol
Llama 4 Maverick
Provider
OpenAI (US)
Meta (US)
Released
September 22, 2026
April 2025
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$2/$10 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment
GPT-6 Sol
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol
GPT-6 Sol
GPT-6 Sol lists openAI says it makes about half as many mistakes as GPT-5.6 Sol among its strengths; Llama 4 Maverick does not.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30)
GPT-6 Sol
GPT-6 Sol lists priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30) among its strengths; Llama 4 Maverick does not.
Open weights, 1M context
Llama 4 Maverick
Open weights make this possible at all — GPT-6 Sol 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-6 Sol is API-only.
Self-hostable
Llama 4 Maverick
Llama 4 Maverick lists self-hostable among its strengths; GPT-6 Sol 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-6 Sol's $2/$10 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-6 Sol, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Sol
Larger 1.05M tokens 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-6 Sol is API-only.
Anyone whose priority is openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment
→ GPT-6 Sol
It is specifically built for that.
Anyone whose priority is open weights, 1m context
→ Llama 4 Maverick
That is its strongest area.
GPT-6 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs are real: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid 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-6 Sol 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-6 Sol 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-6 Sol 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-6 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment 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-6 Sol 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-6 Sol is API-metered at $2/$10 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?
Effectively neither — 1.05M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-6 Sol and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Sol, 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-6 Sol or Llama 4 Maverick?
GPT-6 Sol — released September 22, 2026, about 18 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.