Both are OpenAI models. GPT-6 Astra 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 Astra 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 Astra is openAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Price: GPT-4o mini is about 67× cheaper on input ($0.15/$0.6 per 1M tokens vs $10/$50 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 Astra 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 Astra is the newer model by about 26 months (released September 3, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-4o mini
GPT-6 Astra
Provider
OpenAI (US)
OpenAI (US)
Released
July 18, 2024
September 3, 2026
Context window
128K (~192 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$10/$50 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
96.3%
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 Astra ($10/$50 per 1M tokens), and that gap compounds at volume.
Strong coding for a small model (87.2% HumanEval): GPT-4o mini — GPT-6 Astra is comparatively weak here — trails Meta's Muse Spark 1.3 on some coding evals (DeepSWE v1.1: 74.1 vs 75.4)
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.
Computer & browser use (ScreenSpot-Pro 92.7%): GPT-6 Astra — OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks — and it carries the larger 1.05M tokens context.
Cybersecurity exploit development (ExploitBench 100%): GPT-6 Astra — OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks — and it is the newer of the two.
Frontier math reasoning (FrontierMath Tier 4: 97.6%): GPT-6 Astra — GPT-4o mini is comparatively weak here — weaker on hard reasoning and coding than frontier models
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 Astra — 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 Astra, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Astra — 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 computer & browser use (screenspot-pro 92.7%): GPT-6 Astra — 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 Astra: where it fits
OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. Released September 3, 2026 by OpenAI, it is built for computer & browser use (ScreenSpot-Pro 92.7%), cybersecurity exploit development (ExploitBench 100%), frontier math reasoning (FrontierMath Tier 4: 97.6%), and long-context recall (MRCR v2 512K-1M: 96.3%).
Its trade-offs: no native audio or video input, pricing doubles for prompts over 272K tokens (input/cache 2x, output 1.5x), trails Meta's Muse Spark 1.3 on some coding evals (DeepSWE v1.1: 74.1 vs 75.4), and a separate opt-in "Daybreak" program gives vetted cybersecurity defenders a less-restricted version for legitimate vulnerability research; the public version already refuses ~91.5% of offensive cyber jailbreak attempts by default. At $10 in / $50 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Because GPT-4o mini and GPT-6 Astra come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-6 Astra 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 Astra and drop down only with a concrete reason.
Frequently asked questions
Is GPT-4o mini or GPT-6 Astra 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 Astra leans toward computer & browser use (screenspot-pro 92.7%), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or GPT-6 Astra?
GPT-4o mini is cheaper — $0.15/$0.6 per 1M tokens vs $10/$50 per 1M tokens, roughly 67× apart on input.
Which has the bigger context window?
GPT-6 Astra — 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 Astra?
Since both are OpenAI models, the newer one (GPT-6 Astra) 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 Astra?
GPT-6 Astra — released September 3, 2026, about 26 months after GPT-4o mini.
GPT-4o mini vs GPT-6 Astra
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-6 Astra 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 Astra 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 Astra is openAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. 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 67× cheaper on input ($0.15/$0.6 per 1M tokens vs $10/$50 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 Astra 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 Astra is the newer model by about 26 months (released September 3, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-4o mini
GPT-6 Astra
Provider
OpenAI (US)
OpenAI (US)
Released
July 18, 2024
September 3, 2026
Context window
128K (~192 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$10/$50 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
96.3%
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 Astra ($10/$50 per 1M tokens), and that gap compounds at volume.
Strong coding for a small model (87.2% HumanEval)
GPT-4o mini
GPT-6 Astra is comparatively weak here — trails Meta's Muse Spark 1.3 on some coding evals (DeepSWE v1.1: 74.1 vs 75.4)
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.
Computer & browser use (ScreenSpot-Pro 92.7%)
GPT-6 Astra
OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks — and it carries the larger 1.05M tokens context.
Cybersecurity exploit development (ExploitBench 100%)
GPT-6 Astra
OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks — and it is the newer of the two.
Frontier math reasoning (FrontierMath Tier 4: 97.6%)
GPT-6 Astra
GPT-4o mini is comparatively weak here — weaker on hard reasoning and coding than frontier models
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 Astra
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 Astra, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Astra
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 computer & browser use (screenspot-pro 92.7%)
→ GPT-6 Astra
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 Astra: where it fits
OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. Released September 3, 2026 by OpenAI, it is built for computer & browser use (ScreenSpot-Pro 92.7%), cybersecurity exploit development (ExploitBench 100%), frontier math reasoning (FrontierMath Tier 4: 97.6%), and long-context recall (MRCR v2 512K-1M: 96.3%).
Its trade-offs: no native audio or video input, pricing doubles for prompts over 272K tokens (input/cache 2x, output 1.5x), trails Meta's Muse Spark 1.3 on some coding evals (DeepSWE v1.1: 74.1 vs 75.4), and a separate opt-in "Daybreak" program gives vetted cybersecurity defenders a less-restricted version for legitimate vulnerability research; the public version already refuses ~91.5% of offensive cyber jailbreak attempts by default. At $10 in / $50 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Because GPT-4o mini and GPT-6 Astra come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-6 Astra 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 Astra and drop down only with a concrete reason.
Want both GPT-4o mini and GPT-6 Astra 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.
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 Astra leans toward computer & browser use (screenspot-pro 92.7%), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or GPT-6 Astra?
GPT-4o mini is cheaper — $0.15/$0.6 per 1M tokens vs $10/$50 per 1M tokens, roughly 67× apart on input.
Which has the bigger context window?
GPT-6 Astra — 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 Astra?
Since both are OpenAI models, the newer one (GPT-6 Astra) 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 Astra?
GPT-6 Astra — released September 3, 2026, about 26 months after GPT-4o mini.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.