GLM 5.1 vs MiMo-V2.6-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-V2.6-Pro for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters or 1.02 trillion total parameters, 42b active per token (sparse moe), mit-licensed and self-hostable. On a tight budget at scale, MiMo-V2.6-Pro is the value pick.
GLM 5.1 (Z.ai) and MiMo-V2.6-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-V2.6-Pro is xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: MiMo-V2.6-Pro is about 3.2× cheaper on input ($0.435/$0.87 per 1M tokens vs $1.4/$4.4 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: MiMo-V2.6-Pro holds 5.2× more — 1M tokens (~1,573 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: MiMo-V2.6-Pro is the newer model by about 6 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GLM 5.1 | MiMo-V2.6-Pro |
|---|---|---|
| Provider | Z.ai (China) | Xiaomi (China) |
| Released | April 7, 2026 | September 22, 2026 |
| Context window | 200K (~300 pages) | 1M tokens (~1,573 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 |
| Modalities | text, code | text, image, video, audio |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Long-horizon autonomous agentic engineering (up to 8-hour runs)
GLM 5.1
GLM 5.1 lists long-horizon autonomous agentic engineering (up to 8-hour runs) among its strengths; MiMo-V2.6-Pro does not.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)
GLM 5.1
MiMo-V2.6-Pro is comparatively weak here — first-generation omnimodal release from Xiaomi's MiMo line — benchmark claims are largely Xiaomi's own reporting, not yet widely independently verified
Sustained tool use across thousands of calls
GLM 5.1
GLM 5.1 lists sustained tool use across thousands of calls among its strengths; MiMo-V2.6-Pro does not.
Natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
MiMo-V2.6-Pro
GLM 5.1 is comparatively weak here — text-only, with no image, audio, or video input
1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable
MiMo-V2.6-Pro
Its 1M tokens window holds about 5.2× more than GLM 5.1's 200K in a single prompt.
Reported Artificial Analysis Intelligence Index score of 46
MiMo-V2.6-Pro
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026 — and it runs cheaper at $0.435/$0.87 per 1M tokens.
Lowest cost at scale
MiMo-V2.6-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-V2.6-Pro
Its 1M tokens window is about 5.2× larger than GLM 5.1's 200K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.6-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-V2.6-Pro
Larger 1M tokens 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 natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
→ MiMo-V2.6-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-V2.6-Pro: where it fits
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. Released September 22, 2026 by Xiaomi, it is built for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, 1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable, reported Artificial Analysis Intelligence Index score of 46, and a separate 'UltraSpeed' variant reportedly delivers up to 20x faster output than Pro at similar quality for high-throughput use cases.
Its trade-offs: first-generation omnimodal release from Xiaomi's MiMo line — benchmark claims are largely Xiaomi's own reporting, not yet widely independently verified, an Artificial Analysis Index score of 46 trails several established frontier models, and no official API pricing from Xiaomi directly — the listed price reflects third-party inference providers (e.g. OpenRouter), which can change independently of Xiaomi's own terms. 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-V2.6-Pro overlap enough that the right pick depends on your specific job. MiMo-V2.6-Pro costs less per token; MiMo-V2.6-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-V2.6-Pro for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both GLM 5.1 and MiMo-V2.6-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 pricingFrequently asked questions
Is GLM 5.1 or MiMo-V2.6-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-V2.6-Pro leans toward natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5.1 or MiMo-V2.6-Pro?
MiMo-V2.6-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-V2.6-Pro — 1M tokens vs 200K, about 5.2× 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-V2.6-Pro together?
Yes — a multi-model platform like LumiChats gives you GLM 5.1, MiMo-V2.6-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-V2.6-Pro?
MiMo-V2.6-Pro — released September 22, 2026, about 6 months 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.