GPT-6.1 Terra vs Laguna XS 2.1
OpenAI · US | Poolside · 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 Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. Choose Laguna XS 2.1 if you need self-hosting or data privacy; GPT-6.1 Terra if you want a managed API.
GPT-6.1 Terra (OpenAI) and Laguna XS 2.1 (Poolside) 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. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. 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
- ▸Price: Laguna XS 2.1 is about 10× cheaper on input ($0.1/$0.2 per 1M tokens vs $1/$5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: GPT-6.1 Terra holds 4× more — 1.05M tokens (~1,575 pages) vs 256K (~393 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 4 months (released October 26, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GPT-6.1 Terra | Laguna XS 2.1 |
|---|---|---|
| Provider | OpenAI (US) | Poolside (US) |
| Released | October 26, 2026 | July 2, 2026 |
| Context window | 1.05M tokens (~1,575 pages) | 256K (~393 pages) |
| Price (in/out) | $1/$5 per 1M tokens | $0.1/$0.2 per 1M tokens |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, code | text, code |
| SWE-Bench Verified | Not published | 70.9% |
| MRCR v2 @ 1M | Not published | Not published |
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
Its 1.05M tokens window holds about 4× more than Laguna XS 2.1's 256K in a single prompt.
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
Laguna XS 2.1 is comparatively weak here — weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise
1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API
GPT-6.1 Terra
Laguna XS 2.1 is comparatively weak here — the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters
Laguna XS 2.1
GPT-6.1 Terra is comparatively weak here — benchmark figures are vendor-reported; no SWE-bench Verified or MRCR numbers published
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime
Laguna XS 2.1
Open weights make this possible at all — GPT-6.1 Terra is API-only, so it cannot leave the vendor's servers.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens it undercuts GPT-6.1 Terra ($1/$5 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-6.1 Terra
Its 1.05M tokens window is about 4× larger than Laguna XS 2.1's 256K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Laguna XS 2.1
At $0.1/$0.2 per 1M tokens it undercuts GPT-6.1 Terra, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6.1 Terra
Larger 1.05M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Laguna XS 2.1
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 remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters
→ Laguna XS 2.1
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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. Laguna XS 2.1 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 Laguna XS 2.1 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 Laguna XS 2.1 better for coding?
Public SWE-Bench figures are not available for GPT-6.1 Terra, 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 Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6.1 Terra or Laguna XS 2.1?
Laguna XS 2.1 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?
GPT-6.1 Terra — 1.05M tokens vs 256K, about 4× 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 Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you GPT-6.1 Terra, Laguna XS 2.1 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 Laguna XS 2.1?
GPT-6.1 Terra — released October 26, 2026, about 4 months after Laguna XS 2.1.
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.