GPT-4o mini vs GPT-6.1 Terra
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-6.1 Terra is the newer, generally stronger default; reach for GPT-4o mini when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-4o mini and GPT-6.1 Terra are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-4o mini is openAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. 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. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
- ▸Price: GPT-4o mini is about 6.7× cheaper on input ($0.15/$0.6 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 8.2× more — 1.05M tokens (~1,575 pages) vs 128K (~192 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 28 months (released October 26, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GPT-4o mini | GPT-6.1 Terra |
|---|---|---|
| Provider | OpenAI (US) | OpenAI (US) |
| Released | July 18, 2024 | October 26, 2026 |
| Context window | 128K (~192 pages) | 1.05M tokens (~1,575 pages) |
| Price (in/out) | $0.15/$0.6 per 1M tokens | $1/$5 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image | text, image, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Very low cost per token for its capability tier
GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts GPT-6.1 Terra ($1/$5 per 1M tokens), and that gap compounds at volume.
Strong coding for a small model (87.2% HumanEval)
GPT-4o mini
GPT-6.1 Terra is comparatively weak here — openAI still positions Sol and Astra as the higher-capability choices for demanding coding problems
Leading MMLU among peer small models (82%)
GPT-4o mini
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch — and it runs cheaper at $0.15/$0.6 per 1M tokens.
$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 8.2× more than GPT-4o mini's 128K 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
GPT-4o mini is comparatively weak here — weaker on hard reasoning and coding than frontier models
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-4o mini is comparatively weak here — only 128K context with an October 2023 knowledge cutoff
Lowest cost at scale
GPT-4o mini
At $0.15/$0.6 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 8.2× larger than GPT-4o mini's 128K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-4o mini
At $0.15/$0.6 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.
Anyone whose priority is very low cost per token for its capability tier
→ GPT-4o mini
It is specifically built for that.
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
That is its strongest area.
GPT-4o mini: where it fits
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Released July 18, 2024 by OpenAI, it is built for very low cost per token for its capability tier, strong coding for a small model (87.2% HumanEval), leading MMLU among peer small models (82%), and text and image (vision) understanding in the API.
Its trade-offs are real: only 128K context with an October 2023 knowledge cutoff, and weaker on hard reasoning and coding than frontier models. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
Because GPT-4o mini and GPT-6.1 Terra come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-6.1 Terra is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GPT-6.1 Terra and drop down only with a concrete reason.
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See pricingFrequently asked questions
Is GPT-4o mini or GPT-6.1 Terra 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-4o mini leans toward very low cost per token for its capability tier while 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, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or GPT-6.1 Terra?
GPT-4o mini is cheaper — $0.15/$0.6 per 1M tokens vs $1/$5 per 1M tokens, roughly 6.7× apart on input.
Which has the bigger context window?
GPT-6.1 Terra — 1.05M tokens vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GPT-4o mini to GPT-6.1 Terra?
Since both are OpenAI models, the newer one (GPT-6.1 Terra) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-4o mini or GPT-6.1 Terra?
GPT-6.1 Terra — released October 26, 2026, about 28 months after GPT-4o mini.
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.