GLM-5.3-Flash vs DeepSeek Flash (4.1)
GLM-5.3-Flash scores higher on the Models at Work leaderboard (79 vs 42 out of 100). GLM-5.3-Flash is about 2.2× cheaper per blended million tokens ($0.24 vs $0.52).
| GLM-5.3-Flash · Z.ai | DeepSeek Flash (4.1) · DeepSeek | |
|---|---|---|
| Leaderboard rank | #9 | #26 |
| Score (0–100) | 79 | 42 |
| Tier | Open weights | Fast and cheap |
| Price per 1M tokens | $0.15 in · $0.50 out | $0.30 in · $1.20 out |
| Context window | 1M | 1M |
| Open weights | Yes | Not verified |
| Artificial Analysis Intelligence Index | 42 | — |
| Arena Text score | 1475 (rank 38) | — |
| Arena WebDev score | 1609 (rank 26) | — |
| Best for | Cheap agentic coding execution, Bulk document and image processing, Self-hosted multimodal assistants | Cheap coding tiers, Bulk generation, Experiments where data residency is not a constraint |
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.
Choose DeepSeek Flash (4.1) if…
- you need cheap coding tiers
- you need bulk generation
- you need experiments where data residency is not a constraint
The reason a thousand people argued on Hacker News this week: frontier-adjacent coding for pocket change, with the caveats you would expect.
Caveats: Open-weights status and licence not verified from a primary source at time of writing. Off-peak and peak pricing differ; the cheap numbers are off-peak. Data handling terms should be read before any enterprise use.
What practitioners say
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'.
DeepSeek Flash (4.1): The 'why isn't the industry freaking out' post hit 1,067 points; the most-upvoted replies say the price is real and the coding gap to Opus is also real.
Questions people ask
Which is better, GLM-5.3-Flash or DeepSeek Flash (4.1)?
GLM-5.3-Flash scores higher on the Models at Work leaderboard (79 vs 42 out of 100). GLM-5.3-Flash is about 2.2× cheaper per blended million tokens ($0.24 vs $0.52).
When should I choose GLM-5.3-Flash over DeepSeek Flash (4.1)?
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.
When should I choose DeepSeek Flash (4.1) over GLM-5.3-Flash?
Choose DeepSeek Flash (4.1) for cheap coding tiers, bulk generation, experiments where data residency is not a constraint. The reason a thousand people argued on Hacker News this week: frontier-adjacent coding for pocket change, with the caveats you would expect.
Which is cheaper, GLM-5.3-Flash or DeepSeek Flash (4.1)?
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). DeepSeek Flash (4.1) costs $0.30 per million input tokens and $1.20 per million output tokens on DeepSeek's list price (DeepSeek API 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.