MiMo-V2.5-Pro vs Reflection Beam 1.0
Xiaomi · China | Reflection AI · US · Updated June 2026
Quick verdict
Pick MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro) or long-horizon autonomous tasks (1,000+ tool calls). Pick Reflection Beam 1.0 for 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0 or reflection claims 3-4x less inference compute than rival models (vendor claim). On a tight budget at scale, Reflection Beam 1.0 is the value pick.
MiMo-V2.5-Pro (Xiaomi, China) and Reflection Beam 1.0 (Reflection AI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Reflection Beam 1.0 is reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Reflection Beam 1.0 is the newer model by about 6 months (released October 16, 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 | MiMo-V2.5-Pro | Reflection Beam 1.0 |
|---|---|---|
| Provider | Xiaomi (China) | Reflection AI (US) |
| Released | April 22, 2026 | October 16, 2026 |
| Context window | 1M (~1,500 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $0.435/$0.87 per 1M tokens | Open weight (self-host / free) |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, image, video, code | text, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Complex software engineering (top-ranked on SWE-bench Pro)
MiMo-V2.5-Pro
Reflection Beam 1.0 is comparatively weak here — headline benchmarks come from Reflection's own model card; independent evaluation was limited at launch
Long-horizon autonomous tasks (1,000+ tool calls)
MiMo-V2.5-Pro
MiMo-V2.5-Pro lists long-horizon autonomous tasks (1,000+ tool calls) among its strengths; Reflection Beam 1.0 does not.
Strong on GDPVal and ClawEval
MiMo-V2.5-Pro
MiMo-V2.5-Pro lists strong on GDPVal and ClawEval among its strengths; Reflection Beam 1.0 does not.
501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and it is the newer of the two.
Reflection claims 3-4x less inference compute than rival models (vendor claim)
Reflection Beam 1.0
MiMo-V2.5-Pro is comparatively weak here — benchmark rankings are largely vendor-stated
Fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task
Reflection Beam 1.0
Reflection Beam 1.0 lists fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task among its strengths; MiMo-V2.5-Pro does not.
Lowest cost at scale
Reflection Beam 1.0
Its weights are open, so at volume you pay for your own hardware instead of MiMo-V2.5-Pro's $0.435/$0.87 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Reflection Beam 1.0
At Open weight (self-host / free) it undercuts MiMo-V2.5-Pro, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is complex software engineering (top-ranked on swe-bench pro)
→ MiMo-V2.5-Pro
It is specifically built for that.
Anyone whose priority is 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0
→ Reflection Beam 1.0
That is its strongest area.
An enterprise with regional data-residency rules
→ Reflection Beam 1.0 or MiMo-V2.5-Pro
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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 are real: 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.
Reflection Beam 1.0: where it fits
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. Released October 16, 2026 by Reflection AI, it is built for 501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0, reflection claims 3-4x less inference compute than rival models (vendor claim), fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task, and third-party hosts list it from $0.25/$1.00 per million tokens (Nebius, as of Oct 27); Reflection's own API is in free beta.
Its trade-offs: artificial Analysis Intelligence Index of 30, well below DeepSeek V4.1 Flash and GLM-5.3 (45), text-only input; some users report reasoning loops on long agent runs, self-hosting needs about 353 GB of GPU memory even at NVFP4, and kernels are CUDA-only for now, and headline benchmarks come from Reflection's own model card; independent evaluation was limited at launch. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." MiMo-V2.5-Pro (China) and Reflection Beam 1.0 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Reflection Beam 1.0 is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both MiMo-V2.5-Pro and Reflection Beam 1.0 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 MiMo-V2.5-Pro or Reflection Beam 1.0 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, MiMo-V2.5-Pro leans toward complex software engineering (top-ranked on swe-bench pro) while Reflection Beam 1.0 leans toward 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5-Pro or Reflection Beam 1.0?
Reflection Beam 1.0 is cheaper — $0.435/$0.87 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both MiMo-V2.5-Pro and Reflection Beam 1.0 together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5-Pro, Reflection Beam 1.0 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, MiMo-V2.5-Pro or Reflection Beam 1.0?
Reflection Beam 1.0 — released October 16, 2026, about 6 months after MiMo-V2.5-Pro.
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.