GLM 5.1 vs MiMo-V2.5-Pro

Z.ai · China  |  Xiaomi · China · Updated June 2026

Quick verdict

Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Pick MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro) or long-horizon autonomous tasks (1,000+ tool calls). On a tight budget at scale, MiMo-V2.5-Pro is the value pick.

GLM 5.1 (Z.ai) and MiMo-V2.5-Pro (Xiaomi) are two of the models people most often weigh against each other in 2026. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. 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

SpecGLM 5.1MiMo-V2.5-Pro
ProviderZ.ai (China) Xiaomi (China)
ReleasedApril 7, 2026 April 22, 2026
Context window200K (~300 pages) 1M (~1,500 pages)
Price (in/out)$1.4/$4.4 per 1M tokens $0.435/$0.87 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, code text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Long-horizon autonomous agentic engineering (up to 8-hour runs)

GLM 5.1

A core design strength of GLM 5.1.

State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)

GLM 5.1

A core design strength of GLM 5.1.

Sustained tool use across thousands of calls

GLM 5.1

A core design strength of GLM 5.1.

Complex software engineering (top-ranked on SWE-bench Pro)

MiMo-V2.5-Pro

A core design strength of MiMo-V2.5-Pro.

Long-horizon autonomous tasks (1,000+ tool calls)

MiMo-V2.5-Pro

A core design strength of MiMo-V2.5-Pro.

Strong on GDPVal and ClawEval

MiMo-V2.5-Pro

A core design strength of MiMo-V2.5-Pro.

Lowest cost at scale

MiMo-V2.5-Pro

At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

MiMo-V2.5-Pro

Its 1M window is about 5× larger, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

MiMo-V2.5-Pro

At $0.435/$0.87 per 1M tokens it undercuts GLM 5.1, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

MiMo-V2.5-Pro

Larger 1M window fits more in one prompt.

Anyone whose priority is long-horizon autonomous agentic engineering (up to 8-hour runs)

GLM 5.1

It is specifically built for that.

Anyone whose priority is complex software engineering (top-ranked on swe-bench pro)

MiMo-V2.5-Pro

That is its strongest area.

GLM 5.1: where it fits

An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.

Its trade-offs are real: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 out per million tokens, it sits in the mid price band.

MiMo-V2.5-Pro: where it fits

Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Released April 22, 2026 by Xiaomi, it is built for complex software engineering (top-ranked on SWE-bench Pro), long-horizon autonomous tasks (1,000+ tool calls), strong on GDPVal and ClawEval, and agent-framework integration.

Its trade-offs: benchmark rankings are largely vendor-stated, and limited Western adoption and tooling. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

GLM 5.1 and MiMo-V2.5-Pro overlap enough that the right pick depends on your specific job. MiMo-V2.5-Pro costs less per token; MiMo-V2.5-Pro holds the larger context; and each leads in its own area — GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs), MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro). Rather than crowning one, run the same hard task through both once and let the results decide.

Want both GLM 5.1 and MiMo-V2.5-Pro 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 GLM 5.1 or MiMo-V2.5-Pro 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, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) while MiMo-V2.5-Pro leans toward complex software engineering (top-ranked on swe-bench pro), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GLM 5.1 or MiMo-V2.5-Pro?

MiMo-V2.5-Pro is cheaper — $1.4/$4.4 per 1M tokens vs $0.435/$0.87 per 1M tokens, roughly 3.2× apart on input.

Which has the bigger context window?

MiMo-V2.5-Pro — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GLM 5.1 and MiMo-V2.5-Pro together?

Yes — a multi-model platform like LumiChats gives you GLM 5.1, MiMo-V2.5-Pro 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 5.1 or MiMo-V2.5-Pro?

MiMo-V2.5-Pro — released April 22, 2026, about 15 days after GLM 5.1.

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.