GPT-5.2 vs Mercury 2.5 Preview

OpenAI · US  |  Inception Labs · US · Updated June 2026

Quick verdict

Pick GPT-5.2 for strong all-round reasoning or reliable structured output. 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-5.2 (OpenAI) and Mercury 2.5 Preview (Inception Labs) are two of the models people most often weigh against each other in 2026. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. 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

Side-by-side specs

SpecGPT-5.2Mercury 2.5 Preview
ProviderOpenAI (US) Inception Labs (US)
ReleasedDecember 11, 2025 August 31, 2026
Context window400K (~600 pages) 260K tokens (~390 pages)
Price (in/out)$1.75/$14 per 1M tokens $0.04/$0.15 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image, code text
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Strong all-round reasoning

GPT-5.2

A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5 — and it carries the larger 400K context.

Reliable structured output

GPT-5.2

GPT-5.2 lists reliable structured output among its strengths; Mercury 2.5 Preview does not.

Broad ecosystem and tooling

GPT-5.2

GPT-5.2 lists broad ecosystem and tooling 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

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.

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-5.2 ($1.75/$14 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 is the newer of the two.

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

GPT-5.2

Its 400K window is about 1.5× larger than Mercury 2.5 Preview's 260K tokens, fitting roughly 600 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-5.2, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

GPT-5.2

Larger 400K window fits more in one prompt.

Anyone whose priority is strong all-round reasoning

GPT-5.2

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-5.2: where it fits

A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Released December 11, 2025 by OpenAI, it is built for strong all-round reasoning, reliable structured output, broad ecosystem and tooling, and professional workflows.

Its trade-offs are real: superseded by GPT-5.5, and smaller context than flagships. At $1.75 in / $14 out per million tokens, it sits in the mid 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-5.2 and Mercury 2.5 Preview overlap enough that the right pick depends on your specific job. Mercury 2.5 Preview costs less per token; GPT-5.2 holds the larger context; and each leads in its own area — GPT-5.2 for strong all-round reasoning, 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-5.2 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.

See pricing

Frequently asked questions

Is GPT-5.2 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-5.2 leans toward strong all-round reasoning 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-5.2 or Mercury 2.5 Preview?

Mercury 2.5 Preview is cheaper — $1.75/$14 per 1M tokens vs $0.04/$0.15 per 1M tokens, roughly 44× apart on input.

Which has the bigger context window?

GPT-5.2 — 400K vs 260K tokens, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GPT-5.2 and Mercury 2.5 Preview together?

Yes — a multi-model platform like LumiChats gives you GPT-5.2, 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-5.2 or Mercury 2.5 Preview?

Mercury 2.5 Preview — released August 31, 2026, about 9 months after GPT-5.2.

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.