GLM 5 vs Mercury 2.5 Preview
Z.ai · China | Inception Labs · US · Updated June 2026
Quick verdict
Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. 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). Choose GLM 5 if you need self-hosting or data privacy; Mercury 2.5 Preview if you want a managed API.
GLM 5 (Z.ai, China) and Mercury 2.5 Preview (Inception Labs, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Mercury 2.5 Preview is about 25× cheaper on input ($0.04/$0.15 per 1M tokens vs $1/$3.2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: Mercury 2.5 Preview holds 1.3× more — 260K tokens (~390 pages) vs 200K (~300 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 7 months (released August 31, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | GLM 5 | Mercury 2.5 Preview |
|---|---|---|
| Provider | Z.ai (China) | Inception Labs (US) |
| Released | February 12, 2026 | August 31, 2026 |
| Context window | 200K (~300 pages) | 260K tokens (~390 pages) |
| Price (in/out) | $1/$3.2 per 1M tokens | $0.04/$0.15 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, code | text |
| SWE-Bench Verified | 77.8% | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Agentic planning and long-horizon coding workflows
GLM 5
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding — and its weights are open while Mercury 2.5 Preview is API-only.
Complex systems design and backend reasoning
GLM 5
GLM 5 lists complex systems design and backend reasoning among its strengths; Mercury 2.5 Preview does not.
Iterative self-correction on autonomous tasks
GLM 5
GLM 5 lists iterative self-correction on autonomous tasks 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 1.3× more than GLM 5's 200K 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 GLM 5 ($1/$3.2 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 1.3× larger than GLM 5's 200K, 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 GLM 5, 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.
A team with data-privacy or self-hosting needs
→ GLM 5
Open weights let you run it on your own hardware; Mercury 2.5 Preview is API-only.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
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.
An enterprise with regional data-residency rules
→ Mercury 2.5 Preview or GLM 5
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 12, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 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
The defining split here is open vs. closed. GLM 5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Mercury 2.5 Preview 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 GLM 5 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 pricingFrequently asked questions
Is GLM 5 or Mercury 2.5 Preview better for coding?
Public SWE-Bench figures are not available for Mercury 2.5 Preview, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5 leans toward agentic planning and long-horizon coding workflows 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, GLM 5 or Mercury 2.5 Preview?
GLM 5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mercury 2.5 Preview is API-metered at $0.04/$0.15 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?
Mercury 2.5 Preview — 260K tokens vs 200K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and Mercury 2.5 Preview together?
Yes — a multi-model platform like LumiChats gives you GLM 5, 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, GLM 5 or Mercury 2.5 Preview?
Mercury 2.5 Preview — released August 31, 2026, about 7 months after GLM 5.
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.