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 Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4) or cost efficiency: ~1/9th the training cost of qwen3.7-plus, ~12x cheaper api than flagship qwen3.8-max. On a tight budget at scale, Qwen3.8-Flash-Next is the value pick.
MiMo-V2.5-Pro (Xiaomi) and Qwen3.8-Flash-Next (Alibaba) are two of the models people most often weigh against each other in 2026. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Qwen3.8-Flash-Next is alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Qwen3.8-Flash-Next is about 2.7× cheaper on input ($0.16/$0.47 per 1M tokens vs $0.435/$0.87 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: MiMo-V2.5-Pro holds 3.8× more — 1M (~1,500 pages) vs 262K tokens natively (extensible to 1M with YaRN) (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Qwen3.8-Flash-Next is the newer model by about 4 months (released August 26, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
MiMo-V2.5-Pro
Qwen3.8-Flash-Next
Provider
Xiaomi (China)
Alibaba (China)
Released
April 22, 2026
August 26, 2026
Context window
1M (~1,500 pages)
262K tokens natively (extensible to 1M with YaRN) (~393 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
$0.16/$0.47 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, video, code
text, image, video
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 — Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost — and it carries the larger 1M context.
Long-horizon autonomous tasks (1,000+ tool calls): MiMo-V2.5-Pro — Its 1M window holds about 3.8× more than Qwen3.8-Flash-Next's 262K tokens natively (extensible to 1M with YaRN) in a single prompt.
Strong on GDPVal and ClawEval: MiMo-V2.5-Pro — MiMo-V2.5-Pro lists strong on GDPVal and ClawEval among its strengths; Qwen3.8-Flash-Next does not.
SWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4): Qwen3.8-Flash-Next — MiMo-V2.5-Pro is comparatively weak here — benchmark rankings are largely vendor-stated
Cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max: Qwen3.8-Flash-Next — At $0.16/$0.47 per 1M tokens it undercuts MiMo-V2.5-Pro ($0.435/$0.87 per 1M tokens), and that gap compounds at volume.
Vision-based agentic tasks (AndroidWorld: 84.5): Qwen3.8-Flash-Next — Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max — and it runs cheaper at $0.16/$0.47 per 1M tokens.
Lowest cost at scale: Qwen3.8-Flash-Next — At $0.16/$0.47 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 3.8× larger than Qwen3.8-Flash-Next's 262K tokens natively (extensible to 1M with YaRN), fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen3.8-Flash-Next — At $0.16/$0.47 per 1M tokens it undercuts MiMo-V2.5-Pro, 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 complex software engineering (top-ranked on swe-bench pro): MiMo-V2.5-Pro — It is specifically built for that.
Anyone whose priority is swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4): Qwen3.8-Flash-Next — That is its strongest area.
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.
Qwen3.8-Flash-Next: where it fits
Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. Released August 26, 2026 by Alibaba, it is built for sWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4), cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max, vision-based agentic tasks (AndroidWorld: 84.5), and previews Qwen4's hybrid gated-DeltaNet plus sparse-attention architecture.
Its trade-offs: trails Claude Opus 4.6 Max on Humanity's Last Exam (35.9 vs 40.0), lower OSWorld 2.0 binary success rate (19.4%), and an open-weight architecture preview rather than Alibaba's polished flagship product. At $0.16 in / $0.47 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
MiMo-V2.5-Pro and Qwen3.8-Flash-Next overlap enough that the right pick depends on your specific job. Qwen3.8-Flash-Next costs less per token; MiMo-V2.5-Pro holds the larger context; and each leads in its own area — MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro), Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is MiMo-V2.5-Pro or Qwen3.8-Flash-Next 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 Qwen3.8-Flash-Next leans toward swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5-Pro or Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next is cheaper — $0.435/$0.87 per 1M tokens vs $0.16/$0.47 per 1M tokens, roughly 2.7× apart on input.
Which has the bigger context window?
MiMo-V2.5-Pro — 1M vs 262K tokens natively (extensible to 1M with YaRN), about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both MiMo-V2.5-Pro and Qwen3.8-Flash-Next together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5-Pro, Qwen3.8-Flash-Next 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 Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next — released August 26, 2026, about 4 months after MiMo-V2.5-Pro.
MiMo-V2.5-Pro vs Qwen3.8-Flash-Next
Xiaomi · China | Alibaba · China · 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 Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4) or cost efficiency: ~1/9th the training cost of qwen3.7-plus, ~12x cheaper api than flagship qwen3.8-max. On a tight budget at scale, Qwen3.8-Flash-Next is the value pick.
MiMo-V2.5-Pro (Xiaomi) and Qwen3.8-Flash-Next (Alibaba) are two of the models people most often weigh against each other in 2026. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Qwen3.8-Flash-Next is alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Qwen3.8-Flash-Next is about 2.7× cheaper on input ($0.16/$0.47 per 1M tokens vs $0.435/$0.87 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: MiMo-V2.5-Pro holds 3.8× more — 1M (~1,500 pages) vs 262K tokens natively (extensible to 1M with YaRN) (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Qwen3.8-Flash-Next is the newer model by about 4 months (released August 26, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
MiMo-V2.5-Pro
Qwen3.8-Flash-Next
Provider
Xiaomi (China)
Alibaba (China)
Released
April 22, 2026
August 26, 2026
Context window
1M (~1,500 pages)
262K tokens natively (extensible to 1M with YaRN) (~393 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
$0.16/$0.47 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, video, code
text, image, video
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
Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost — and it carries the larger 1M context.
Long-horizon autonomous tasks (1,000+ tool calls)
MiMo-V2.5-Pro
Its 1M window holds about 3.8× more than Qwen3.8-Flash-Next's 262K tokens natively (extensible to 1M with YaRN) in a single prompt.
Strong on GDPVal and ClawEval
MiMo-V2.5-Pro
MiMo-V2.5-Pro lists strong on GDPVal and ClawEval among its strengths; Qwen3.8-Flash-Next does not.
SWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4)
Qwen3.8-Flash-Next
MiMo-V2.5-Pro is comparatively weak here — benchmark rankings are largely vendor-stated
Cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max
Qwen3.8-Flash-Next
At $0.16/$0.47 per 1M tokens it undercuts MiMo-V2.5-Pro ($0.435/$0.87 per 1M tokens), and that gap compounds at volume.
Vision-based agentic tasks (AndroidWorld: 84.5)
Qwen3.8-Flash-Next
Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max — and it runs cheaper at $0.16/$0.47 per 1M tokens.
Lowest cost at scale
Qwen3.8-Flash-Next
At $0.16/$0.47 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 3.8× larger than Qwen3.8-Flash-Next's 262K tokens natively (extensible to 1M with YaRN), fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3.8-Flash-Next
At $0.16/$0.47 per 1M tokens it undercuts MiMo-V2.5-Pro, 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 complex software engineering (top-ranked on swe-bench pro)
→ MiMo-V2.5-Pro
It is specifically built for that.
Anyone whose priority is swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4)
→ Qwen3.8-Flash-Next
That is its strongest area.
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.
Qwen3.8-Flash-Next: where it fits
Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. Released August 26, 2026 by Alibaba, it is built for sWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4), cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max, vision-based agentic tasks (AndroidWorld: 84.5), and previews Qwen4's hybrid gated-DeltaNet plus sparse-attention architecture.
Its trade-offs: trails Claude Opus 4.6 Max on Humanity's Last Exam (35.9 vs 40.0), lower OSWorld 2.0 binary success rate (19.4%), and an open-weight architecture preview rather than Alibaba's polished flagship product. At $0.16 in / $0.47 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
MiMo-V2.5-Pro and Qwen3.8-Flash-Next overlap enough that the right pick depends on your specific job. Qwen3.8-Flash-Next costs less per token; MiMo-V2.5-Pro holds the larger context; and each leads in its own area — MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro), Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both MiMo-V2.5-Pro and Qwen3.8-Flash-Next 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.
Is MiMo-V2.5-Pro or Qwen3.8-Flash-Next 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 Qwen3.8-Flash-Next leans toward swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5-Pro or Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next is cheaper — $0.435/$0.87 per 1M tokens vs $0.16/$0.47 per 1M tokens, roughly 2.7× apart on input.
Which has the bigger context window?
MiMo-V2.5-Pro — 1M vs 262K tokens natively (extensible to 1M with YaRN), about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both MiMo-V2.5-Pro and Qwen3.8-Flash-Next together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5-Pro, Qwen3.8-Flash-Next 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 Qwen3.8-Flash-Next?
Qwen3.8-Flash-Next — released August 26, 2026, about 4 months after MiMo-V2.5-Pro.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.