MiMo-V2.6-Pro vs GLM-5.3-Flash
MiMo-V2.6-Pro and GLM-5.3-Flash are within three points on the Models at Work leaderboard, which we treat as a tie (81 vs 79). GLM-5.3-Flash is about 2.3× cheaper per blended million tokens ($0.24 vs $0.54). On Artificial Analysis' independent Intelligence Index, MiMo-V2.6-Pro leads 46 to 42.
| MiMo-V2.6-Pro · Xiaomi | GLM-5.3-Flash · Z.ai | |
|---|---|---|
| Leaderboard rank | #7 | #9 |
| Score (0–100) | 81 | 79 |
| Tier | Open weights | Open weights |
| Price per 1M tokens | $0.43 in · $0.87 out | $0.15 in · $0.50 out |
| Context window | 1M | 1M |
| Open weights | Yes | Yes |
| Artificial Analysis Intelligence Index | 46 | 42 |
| Arena Text score | 1480 (rank 26) | 1475 (rank 38) |
| Arena WebDev score | 1629 (rank 19) | 1609 (rank 26) |
| Best for | Self-hosted agentic coding, Cheap frontier-class batch reasoning, Replacing closed mid-tier models | Cheap agentic coding execution, Bulk document and image processing, Self-hosted multimodal assistants |
Choose MiMo-V2.6-Pro if…
- you need self-hosted agentic coding
- you need cheap frontier-class batch reasoning
- you need replacing closed mid-tier models
The strongest open-weight model right now and absurdly cheap for what it does. MIT-licensed 1T MoE that lands within a few points of Muse Spark and Grok 4.7. Slow-ish and verbose, so budget for latency and thinking tokens.
Caveats: Overthinks: long, repetitive reasoning traces on simple edits; AA flags it as verbose vs the median model. ~47 tok/s on the first-party API is slow next to Gemini Flash or Haiku-class models. Only 4k Arena votes so far; the rank is still settling.
Choose GLM-5.3-Flash if…
- you need cheap agentic coding execution
- you need bulk document and image processing
- you need self-hosted multimodal assistants
Probably the best price-to-intelligence ratio on the market: AA 42 for $0.15/$0.50, MIT-licensed, natively multimodal, 1M context. Not actually fast despite the name; treat it as a cheap executor behind a stronger planner.
Caveats: 'Too slow for execution, despite the name' on Z.ai's own hosting (~60 tok/s); third-party hosts vary. Users report less consistent output than full GLM-5.3; pair it with a planning model. 320B total params: self-hosting still needs a multi-GPU node.
What practitioners say
MiMo-V2.6-Pro: HN (1,130 points) was won over less by scores than by Xiaomi's transparency: a live training dashboard with loss curves, dropped datasets and running cost estimates. Users call it 'incredibly cheap' for Muse-Spark-level benchmarks and say it keeps DeepSeek and GLM 'in check'. Complaints are consistent: 'faster than DeepSeek but still much slower than leading models', and it 'seems to overthink way too much', producing huge reasoning traces for trivial edits. Several recommend it via OpenRouter rather than the Chinese first-party API.
GLM-5.3-Flash: A month-long HN diary ('One month coding with GLM 5.3 Flash', 233 points) spent $68 total; commenters agreed 'a month of agentic coding for $68 is the headline'. The working pattern is 'GLM-5.3 to write the plan, Flash to implement', with one user noting that given an unambiguous plan 'GLM 5.3 Flash executes it just fine'. Negatives: 'too slow for execution, despite the name' on Z.ai hosting, and the full model is 'way more consistent'.
Questions people ask
Which is better, MiMo-V2.6-Pro or GLM-5.3-Flash?
MiMo-V2.6-Pro and GLM-5.3-Flash are within three points on the Models at Work leaderboard, which we treat as a tie (81 vs 79). GLM-5.3-Flash is about 2.3× cheaper per blended million tokens ($0.24 vs $0.54). On Artificial Analysis' independent Intelligence Index, MiMo-V2.6-Pro leads 46 to 42.
When should I choose MiMo-V2.6-Pro over GLM-5.3-Flash?
Choose MiMo-V2.6-Pro for self-hosted agentic coding, cheap frontier-class batch reasoning, replacing closed mid-tier models. The strongest open-weight model right now and absurdly cheap for what it does. MIT-licensed 1T MoE that lands within a few points of Muse Spark and Grok 4.7. Slow-ish and verbose, so budget for latency and thinking tokens.
When should I choose GLM-5.3-Flash over MiMo-V2.6-Pro?
Choose GLM-5.3-Flash for cheap agentic coding execution, bulk document and image processing, self-hosted multimodal assistants. Probably the best price-to-intelligence ratio on the market: AA 42 for $0.15/$0.50, MIT-licensed, natively multimodal, 1M context. Not actually fast despite the name; treat it as a cheap executor behind a stronger planner.
Which is cheaper, MiMo-V2.6-Pro or GLM-5.3-Flash?
MiMo-V2.6-Pro costs $0.43 per million input tokens and $0.87 per million output tokens on Xiaomi's list price (MiMo-V2.6-Pro - Artificial Analysis, read Oct 11, 2026). GLM-5.3-Flash costs $0.15 per million input tokens and $0.50 per million output tokens on Z.ai's list price (Z.ai Pricing, read Oct 11, 2026).
Scores come from the Models at Work leaderboard: Score is 0 to 100 and computed, not typed: 55% independent evals (Artificial Analysis, Arena, Scale SEAL, Epoch, each scaled against its natural floor and the best score in this table, then averaged), 15% blended price on a fixed log scale ($0.05 per million is 100, $60 is 0), 15% practitioner sentiment from Signals and community threads, 15% operational fit (context window, open weights). A missing component drops out and the rest are reweighted. A model with no independent eval yet is provisional and ranks below every measured one. Within three points is a tie. Vendor-published figures are labelled and never counted. Prices are vendor list prices where published; blended figures assume three input tokens per output token.