GLM-5.3 Flash wins on coding (82 vs 78) and price ($0.15 vs $0.3/1M input). For most workflows, GLM-5.3 Flash is the stronger default — native vision and video, mit weights, fifteen cents per million.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GLM-5.3 Flash is the safest overall answer here when you want the strongest default instead of the lowest list price.
Google: Gemini 2.0 Flash is the lower-cost option to start with when you still need useful output at scale.
Gemini 3.5 Flash-Lite is the better pick when response speed matters more than maximum reasoning depth.
GLM-5.3 Flash leads on coding with a score of 82 vs 78 for Gemini 3.5 Flash-Lite.
Gemini 3.5 Flash-Lite has the larger context window: 1.048576M vs 1M for GLM-5.3 Flash.
GLM-5.3 Flash is cheaper at $0.15/1M input tokens vs $0.3/1M for Gemini 3.5 Flash-Lite.
GLM-5.3 Flash is the safer default: it is built for cheap multimodal work at scale on MIT-licensed weights, which covers most of what people bring to this comparison.
Gemini 3.5 Flash-Lite earns its place when your work is mostly high-volume and latency-sensitive workloads at minimal cost, even though it loses the overall count here.
Both models serve different primary workflows — GLM-5.3 Flash for cheap multimodal work at scale on MIT-licensed weights, Gemini 3.5 Flash-Lite for high-volume and latency-sensitive workloads at minimal cost — so running each where it has a clear edge often beats forcing one to do both.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
Z.ai / Budget / Aug 27, 2026
Native vision and video, MIT weights, fifteen cents per million.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need top-tier reasoning or a published SWE-bench Verified figure — this is a volume model, not a ceiling model.
The fastest way to see where the recommendation shifts when your priority changes.
Native vision and video, MIT weights, fifteen cents per million.
Fastest budget multimodal model — 350 tokens/sec at Lite pricing.
Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GLM-5.3 FlashZ.ai | $0.15/1M | $0.50/1M | $2.50 | 1M tokens | Fast | 82 | 76 | 78 |
| Gemini 3.5 Flash-LiteGoogle | $0.30/1M | $2.50/1M | $8.00 | 1.0M tokens | Very fast | 78 | 76 | 78 |
Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.
What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.
A 320B-A18B mixture-of-experts model with native vision and video, MIT-licensed weights and a 1M context — at fifteen cents per million input tokens.
You need top-tier reasoning or a published SWE-bench Verified figure — this is a volume model, not a ceiling model.
The cheapest genuinely multimodal 1M-context model worth using in August 2026. If you are running vision or video at volume and can host weights, nothing at this price is close.
Released August 26, 2026. 320B total parameters, 18B active (320B-A18B MoE). Z.ai lists $0.15/1M input, $0.03/1M cached input and $0.50/1M output, with a launch promotion halving those rates through September 9, 2026. Self-reported against GLM-5.2: DeepSWE 63.4 vs 46.2, AutomationBench 48.8 vs 26.2.
Google's fastest and most cost-effective 3.5-generation model — low-latency, high-throughput agentic workflows at a fraction of Flash pricing.
Pure price-per-benchmark is the criterion — GPT-5.6 Luna wins that math.
The pick when latency matters as much as price — 350 tokens/sec with real agentic chops. GPT-5.6 Luna beats it on raw price and benchmarks, but Flash-Lite is faster and takes video/audio/PDF input.
Released July 21, 2026. Batch pricing $0.15/$1.25; cached input $0.03/1M. Rolling out to Google Search.
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GLM-5.3 Flash wins on more of the categories we score — budget, multimodal, coding — so it is the better default of the two. Gemini 3.5 Flash-Lite is the better pick when your work is mostly high-volume and latency-sensitive workloads at minimal cost. Neither is universally "better": GLM-5.3 Flash is aimed at cheap multimodal work at scale on MIT-licensed weights, Gemini 3.5 Flash-Lite at high-volume and latency-sensitive workloads at minimal cost.
GLM-5.3 Flash is cheaper at $0.15/1M input and $0.5/1M output. Gemini 3.5 Flash-Lite costs $0.3/1M input and $2.5/1M output.
Gemini 3.5 Flash-Lite has the larger context window at 1.048576M tokens vs GLM-5.3 Flash's 1M. For large document analysis, Gemini 3.5 Flash-Lite is the stronger pick.
GLM-5.3 Flash is better for coding with a score of 82 vs Gemini 3.5 Flash-Lite's 78 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.
Gemini 3.5 Flash-Lite is faster with a very fast speed rating (score: 5) vs GLM-5.3 Flash's fast rating (score: 4). Speed matters most for interactive and high-throughput work; for batch jobs the GLM-5.3 Flash latency penalty is usually invisible.
No published SWE-bench Verified score. The launch promotion halves these rates only through September 9, 2026 — the $0.15/$0.50 list price applies after that. Avoid it if you need top-tier reasoning or a published SWE-bench Verified figure — this is a volume model, not a ceiling model. That is the main case for looking at Gemini 3.5 Flash-Lite instead.
Trails full Flash models on hard agentic work (OSWorld 74.0% vs 83.0% for 3.6 Flash). GPT-5.6 Luna undercuts it on per-token price with stronger benchmark scores. Avoid it if pure price-per-benchmark is the criterion — GPT-5.6 Luna wins that math. Against GLM-5.3 Flash specifically, the gap shows up most on coding (82 vs 78).
Take a moderate workload of 10M input and 2M output tokens a month. GLM-5.3 Flash runs $2.50 (at $0.15/1M in and $0.5/1M out); Gemini 3.5 Flash-Lite runs $8.00 (at $0.3/1M in and $2.5/1M out). That is a $5.50/month difference — GLM-5.3 Flash is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is GLM-5.3 Flash for cheap multimodal work at scale on MIT-licensed weights, with Gemini 3.5 Flash-Lite handling high-volume and latency-sensitive workloads at minimal cost. Since GLM-5.3 Flash is both the stronger and the cheaper option here, a split mainly makes sense if Gemini 3.5 Flash-Lite covers a capability you specifically need.