GPT-6.1 Terra vs Llama 4 Scout
OpenAI · US | Meta · US · Updated June 2026
Quick verdict
Pick GPT-6.1 Terra for $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra or terminal-bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for gpt-5.6 terra (openai-reported). Pick Llama 4 Scout for largest advertised context (10m) or open weights, single-gpu friendly. Choose Llama 4 Scout if you need self-hosting or data privacy; GPT-6.1 Terra if you want a managed API.
GPT-6.1 Terra (OpenAI) and Llama 4 Scout (Meta) are two of the models people most often weigh against each other in 2026. GPT-6.1 Terra is openAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. Llama 4 Scout is the 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. 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 Scout ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-6.1 Terra is API-metered at $1/$5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: Llama 4 Scout holds 9.5× more — 10M (~15,000 pages) vs 1.05M tokens (~1,575 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-6.1 Terra is the newer model by about 19 months (released October 26, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GPT-6.1 Terra | Llama 4 Scout |
|---|---|---|
| Provider | OpenAI (US) | Meta (US) |
| Released | October 26, 2026 | April 2025 |
| Context window | 1.05M tokens (~1,575 pages) | 10M (~15,000 pages) |
| Price (in/out) | $1/$5 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 | 15% |
Who wins what
$1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra
GPT-6.1 Terra
OpenAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor — and it is the newer of the two.
Terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported)
GPT-6.1 Terra
Llama 4 Scout is comparatively weak here — ~15% on long-context multi-needle reasoning
1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API
GPT-6.1 Terra
GPT-6.1 Terra lists 1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API among its strengths; Llama 4 Scout does not.
Largest advertised context (10M)
Llama 4 Scout
Its 10M window holds about 9.5× more than GPT-6.1 Terra's 1.05M tokens in a single prompt.
Open weights, single-GPU friendly
Llama 4 Scout
Open weights make this possible at all — GPT-6.1 Terra is API-only, so it cannot leave the vendor's servers.
Self-hosted, data-private deployment
Llama 4 Scout
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller — and it carries the larger 10M context.
Lowest cost at scale
Llama 4 Scout
Its weights are open, so at volume you pay for your own hardware instead of GPT-6.1 Terra's $1/$5 per 1M tokens.
Largest single-prompt input
Llama 4 Scout
Its 10M window is about 9.5× larger than GPT-6.1 Terra's 1.05M tokens, fitting roughly 15,000 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Llama 4 Scout
At Open weight (self-host / free) it undercuts GPT-6.1 Terra, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Llama 4 Scout
Larger 10M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Llama 4 Scout
Open weights let you run it on your own hardware; GPT-6.1 Terra is API-only.
Anyone whose priority is $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra
→ GPT-6.1 Terra
It is specifically built for that.
Anyone whose priority is largest advertised context (10m)
→ Llama 4 Scout
That is its strongest area.
GPT-6.1 Terra: where it fits
OpenAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. Released October 26, 2026 by OpenAI, it is built for $1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra, terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported), 1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API, and error rate on OpenAI's hard-prompt set falls from 53.6% (GPT-5.6 Terra) to 16.7% at low effort and 4.3% at max effort.
Its trade-offs are real: openAI still positions Sol and Astra as the higher-capability choices for demanding coding problems, requests above 272K input tokens are billed at 2x input and 1.5x output for the whole request, closed weights and no fine-tuning support, and benchmark figures are vendor-reported; no SWE-bench Verified or MRCR numbers published. At $1 in / $5 out per million tokens, it sits in the budget price band.
Llama 4 Scout: where it fits
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Released April 2025 by Meta, it is built for largest advertised context (10M), open weights, single-GPU friendly, self-hosted, data-private deployment, and retrieval over very long inputs.
Its trade-offs: effective recall degrades far below 10M, and ~15% on long-context multi-needle 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 Scout gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-6.1 Terra 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-6.1 Terra and Llama 4 Scout 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.
See pricingFrequently asked questions
Is GPT-6.1 Terra or Llama 4 Scout 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-6.1 Terra leans toward $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra while Llama 4 Scout leans toward largest advertised context (10m), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6.1 Terra or Llama 4 Scout?
Llama 4 Scout is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6.1 Terra is API-metered at $1/$5 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 Scout — 10M vs 1.05M tokens, about 9.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-6.1 Terra and Llama 4 Scout together?
Yes — a multi-model platform like LumiChats gives you GPT-6.1 Terra, Llama 4 Scout 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-6.1 Terra or Llama 4 Scout?
GPT-6.1 Terra — released October 26, 2026, about 19 months after Llama 4 Scout.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.