Pick GPT-4o mini for very low cost per token for its capability tier or strong coding for a small model (87.2% humaneval). Pick Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation or coding accuracy (95.7%, 91st percentile among cost-optimized models). On a tight budget at scale, Mercury 2.5 Preview is the value pick.
GPT-4o mini (OpenAI) and Mercury 2.5 Preview (Inception Labs) are two of the models people most often weigh against each other in 2026. 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. Mercury 2.5 Preview is inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Mercury 2.5 Preview is about 3.8× cheaper on input ($0.04/$0.15 per 1M tokens vs $0.15/$0.6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Mercury 2.5 Preview holds 2× more — 260K tokens (~390 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: Mercury 2.5 Preview is the newer model by about 26 months (released August 31, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-4o mini
Mercury 2.5 Preview
Provider
OpenAI (US)
Inception Labs (US)
Released
July 18, 2024
August 31, 2026
Context window
128K (~192 pages)
260K tokens (~390 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$0.04/$0.15 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text
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 — Mercury 2.5 Preview is comparatively weak here — 260K context window is far shorter than frontier 1M-token models
Strong coding for a small model (87.2% HumanEval): GPT-4o mini — GPT-4o mini lists strong coding for a small model (87.2% HumanEval) among its strengths; Mercury 2.5 Preview does not.
Leading MMLU among peer small models (82%): GPT-4o mini — GPT-4o mini lists leading MMLU among peer small models (82%) among its strengths; Mercury 2.5 Preview does not.
Very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation: Mercury 2.5 Preview — Its 260K tokens window holds about 2× more than GPT-4o mini's 128K in a single prompt.
Coding accuracy (95.7%, 91st percentile among cost-optimized models): Mercury 2.5 Preview — At $0.04/$0.15 per 1M tokens it undercuts GPT-4o mini ($0.15/$0.6 per 1M tokens), and that gap compounds at volume.
Mathematics accuracy (97.0%, 97th percentile): Mercury 2.5 Preview — Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality — and it runs cheaper at $0.04/$0.15 per 1M tokens.
Lowest cost at scale: Mercury 2.5 Preview — At $0.04/$0.15 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Mercury 2.5 Preview — Its 260K tokens window is about 2× larger than GPT-4o mini's 128K, fitting roughly 390 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Mercury 2.5 Preview — At $0.04/$0.15 per 1M tokens it undercuts GPT-4o mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Mercury 2.5 Preview — Larger 260K 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 very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation: Mercury 2.5 Preview — 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.
Mercury 2.5 Preview: where it fits
Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. Released August 31, 2026 by Inception Labs, it is built for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, coding accuracy (95.7%, 91st percentile among cost-optimized models), mathematics accuracy (97.0%, 97th percentile), and tunable reasoning levels with parallel tool calls and schema-aligned JSON output.
Its trade-offs: 260K context window is far shorter than frontier 1M-token models, no vision or audio modalities, positioned only against cost-optimized models (GPT-5.6 Luna Low, Gemini 3.5 Flash-Lite), not frontier-class, and current $0.04/$0.15 pricing includes a limited-time launch promotion on OpenRouter (list price is $0.20/$0.75, may rise after Sept 8, 2026). At $0.04 in / $0.15 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
GPT-4o mini and Mercury 2.5 Preview overlap enough that the right pick depends on your specific job. Mercury 2.5 Preview costs less per token; Mercury 2.5 Preview holds the larger context; and each leads in its own area — GPT-4o mini for very low cost per token for its capability tier, Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is GPT-4o mini or Mercury 2.5 Preview 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 Mercury 2.5 Preview leans toward very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or Mercury 2.5 Preview?
Mercury 2.5 Preview is cheaper — $0.15/$0.6 per 1M tokens vs $0.04/$0.15 per 1M tokens, roughly 3.8× apart on input.
Which has the bigger context window?
Mercury 2.5 Preview — 260K tokens vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-4o mini and Mercury 2.5 Preview together?
Yes — a multi-model platform like LumiChats gives you GPT-4o mini, Mercury 2.5 Preview 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-4o mini or Mercury 2.5 Preview?
Mercury 2.5 Preview — released August 31, 2026, about 26 months after GPT-4o mini.
GPT-4o mini vs Mercury 2.5 Preview
OpenAI · US | Inception Labs · US · Updated June 2026
Quick verdict
Pick GPT-4o mini for very low cost per token for its capability tier or strong coding for a small model (87.2% humaneval). Pick Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation or coding accuracy (95.7%, 91st percentile among cost-optimized models). On a tight budget at scale, Mercury 2.5 Preview is the value pick.
GPT-4o mini (OpenAI) and Mercury 2.5 Preview (Inception Labs) are two of the models people most often weigh against each other in 2026. 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. Mercury 2.5 Preview is inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Mercury 2.5 Preview is about 3.8× cheaper on input ($0.04/$0.15 per 1M tokens vs $0.15/$0.6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Mercury 2.5 Preview holds 2× more — 260K tokens (~390 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: Mercury 2.5 Preview is the newer model by about 26 months (released August 31, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-4o mini
Mercury 2.5 Preview
Provider
OpenAI (US)
Inception Labs (US)
Released
July 18, 2024
August 31, 2026
Context window
128K (~192 pages)
260K tokens (~390 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$0.04/$0.15 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text
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
Mercury 2.5 Preview is comparatively weak here — 260K context window is far shorter than frontier 1M-token models
Strong coding for a small model (87.2% HumanEval)
GPT-4o mini
GPT-4o mini lists strong coding for a small model (87.2% HumanEval) among its strengths; Mercury 2.5 Preview does not.
Leading MMLU among peer small models (82%)
GPT-4o mini
GPT-4o mini lists leading MMLU among peer small models (82%) among its strengths; Mercury 2.5 Preview does not.
Very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation
Mercury 2.5 Preview
Its 260K tokens window holds about 2× more than GPT-4o mini's 128K in a single prompt.
Coding accuracy (95.7%, 91st percentile among cost-optimized models)
Mercury 2.5 Preview
At $0.04/$0.15 per 1M tokens it undercuts GPT-4o mini ($0.15/$0.6 per 1M tokens), and that gap compounds at volume.
Mathematics accuracy (97.0%, 97th percentile)
Mercury 2.5 Preview
Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality — and it runs cheaper at $0.04/$0.15 per 1M tokens.
Lowest cost at scale
Mercury 2.5 Preview
At $0.04/$0.15 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Mercury 2.5 Preview
Its 260K tokens window is about 2× larger than GPT-4o mini's 128K, fitting roughly 390 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mercury 2.5 Preview
At $0.04/$0.15 per 1M tokens it undercuts GPT-4o mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Mercury 2.5 Preview
Larger 260K 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 very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation
→ Mercury 2.5 Preview
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.
Mercury 2.5 Preview: where it fits
Inception Labs' August 31, 2026 diffusion-based language model preview, refining tokens in parallel for roughly 10x the throughput of comparable autoregressive models at cost-optimized-tier quality. Released August 31, 2026 by Inception Labs, it is built for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, coding accuracy (95.7%, 91st percentile among cost-optimized models), mathematics accuracy (97.0%, 97th percentile), and tunable reasoning levels with parallel tool calls and schema-aligned JSON output.
Its trade-offs: 260K context window is far shorter than frontier 1M-token models, no vision or audio modalities, positioned only against cost-optimized models (GPT-5.6 Luna Low, Gemini 3.5 Flash-Lite), not frontier-class, and current $0.04/$0.15 pricing includes a limited-time launch promotion on OpenRouter (list price is $0.20/$0.75, may rise after Sept 8, 2026). At $0.04 in / $0.15 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
GPT-4o mini and Mercury 2.5 Preview overlap enough that the right pick depends on your specific job. Mercury 2.5 Preview costs less per token; Mercury 2.5 Preview holds the larger context; and each leads in its own area — GPT-4o mini for very low cost per token for its capability tier, Mercury 2.5 Preview for very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both GPT-4o mini and Mercury 2.5 Preview 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-4o mini or Mercury 2.5 Preview 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 Mercury 2.5 Preview leans toward very high inference throughput (1,107 tok/s) via diffusion-based parallel token generation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or Mercury 2.5 Preview?
Mercury 2.5 Preview is cheaper — $0.15/$0.6 per 1M tokens vs $0.04/$0.15 per 1M tokens, roughly 3.8× apart on input.
Which has the bigger context window?
Mercury 2.5 Preview — 260K tokens vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-4o mini and Mercury 2.5 Preview together?
Yes — a multi-model platform like LumiChats gives you GPT-4o mini, Mercury 2.5 Preview 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-4o mini or Mercury 2.5 Preview?
Mercury 2.5 Preview — released August 31, 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.