GLM 5.3 Flash
- Input / 1M tokens
- $0.04
- Output / 1M tokens
- $0.08
- Providers
- 37
- Uptime, 24 h
- 100%
API models · Side by side
GLM 5.3 Flash vs Gemini 3.8 Flash
GLM 5.3 Flash and Gemini 3.8 Flash can both read text, images and video. GLM is the less expensive API option at the rates below; Gemini can also accept audio and files. That makes this a practical choice between a smaller token bill and the inputs your application needs to handle.
Gemini 3.8 Flash
- Input / 1M tokens
- $0.83
- Output / 1M tokens
- $4.13
- Providers
- 2
- Uptime, 24 h
- 100%
The short answer
Start with GLM for text, screenshot or video tasks when keeping API spending low is the priority. Choose Gemini when the workflow needs direct audio or file input, or already depends on Gemini API features. Both offer about one million tokens of context, so capacity alone does not separate them.
Estimate your monthly bill
Enter your own usage. We apply each model's current rates, including long-prompt pricing, for a 30-day month.
Try:
GLM 5.3 Flash$3.57per month
Gemini 3.8 Flash$111.38per month
A token is roughly three-quarters of an English word. Cached input, reasoning tokens, tools and media are not included.
Compare the details
Compare context, supported inputs and usage costs. Highlighted rows show a difference.
| Feature | GLM 5.3 Flash | Gemini 3.8 Flash |
|---|---|---|
| Input formats | image, text, video | audio, file, image, text, video |
| Output formats | text | text |
| Context / position limit | 1,048,576 | 1,048,576 |
| Endpoint output limit (tokens) | 131,072 | 65,536 |
| Developer features | frequency penalty, Reasoning output, logit bias, logprobs, Output limit, min p, parallel tool calls, presence penalty, Reasoning controls, Thinking effort, repetition penalty, Response format, Seed, Stop sequences, Structured output, Temperature, Tool selection, Tool calling, top k, top logprobs, Sampling controls | Reasoning output, Output limit, Reasoning controls, Thinking effort, Response format, Seed, Stop sequences, Structured output, Temperature, Tool selection, Tool calling, Sampling controls |
| Cached input / 1M tokens | $0.03 | $0.08 |
| Cache write / 1M tokens | Unknown | $0.04 |
| USD input / 1M tokens | $0.04 | $0.83 |
| USD output / 1M tokens | $0.08 | $4.13 |
| Available API providers | 37 | 2 |
| Best provider uptime, last 24 h | 100% | 100% |
| Price range across providers (per 1M tokens) | Input $0.040–$0.22, output $0.078–$0.75 across 37 providers | Set by Google |
| Model identifier | z-ai/glm-5.3-flash | google/gemini-3.8-flash |
API pricing
Prices are in USD per million tokens. Input is what you send; output is what the model generates. Chat subscriptions and API usage are billed separately.
Tools, images and additional reasoning can add charges. The examples below cover input and output tokens only.
Compare local modelsWhat those prices mean in practice
Each example uses the same token budget for both models. These are calculations, not measured workloads. Cache discounts, media, tools and extra reasoning are excluded.
| Workload | GLM 5.3 Flash | Gemini 3.8 Flash |
|---|---|---|
| 1,000 short requestsPer request: 2,000 input + 500 output tokens | $0.12 | $3.71 |
| 100 document summariesPer request: 20,000 input + 1,000 output tokens | $0.09 | $2.06 |
| 10 long-document requestsPer request: 300,000 input + 2,000 output tokens | $0.12 | $2.56 |
Estimate = requests × (input tokens × input price + output tokens × output price) ÷ 1,000,000. Long-prompt rates are applied where the pricing data provides them. Real requests can use different amounts of output.
Beyond the price tag
Short requests make the price gap easy to see
For 1,000 requests with 2,000 input tokens and 500 output tokens each, the base rates in the table produce a total of $0.55 for GLM and $3.7125 for Gemini: about $0.55 versus $3.71. At 1,000 requests a day for 30 days, that becomes $16.50 versus $111.38. These examples use identical token quantities, not identical documents: the models have different tokenizers. They exclude tools, additional reasoning and other separately billed services.
A voice recording changes the shortlist
Gemini accepts audio directly; the GLM endpoint compared here accepts text, images and video. For a recorded support call, Gemini can process the recording without a separate transcription step. With GLM, you would need a transcript or another audio-processing service first. That service has its own cost, and a transcript may omit vocal details. The text-token cost examples do not price an audio workflow.
Screenshots and video are shared ground
Both models accept image and video input and return text. They are therefore candidates for explaining an error screenshot or describing a recorded interface problem. Keep the requested result concrete: identify the error message, the action immediately before it and the evidence for the proposed fix. Supporting video does not establish that a model can identify every relevant event, and neither endpoint here generates video.
Long prompts still need a complete budget
Both compared endpoints allow 1,048,576 tokens of context. The compared rates do not add a prompt-length surcharge. At the displayed base rates, a request with 300,000 input tokens and 2,000 output tokens costs $0.046 on GLM and $0.25575 on Gemini, before extra services. That is about 4.6 cents versus 25.6 cents. Leave room for the answer within the request limits, and avoid resending a whole document collection when only a small part is relevant.
Separate the hosting rate from the developer’s rate
The table and calculator use the compared API routes. GLM is served by multiple hosting companies, and their rates vary. Google’s standard Gemini developer API charges $0.75 per million text, image or video input tokens and $3.75 per million output tokens through December 31, 2026, rising to $1.50 and $7.50 on January 1, 2027; the Gemini route used in this table is $0.825 and $4.125. A bill from a different route can therefore be correct without matching the example. Choose the service you intend to use before setting a production budget.
Set the answer and thinking budgets deliberately
Gemini’s maximum output is 65,536 tokens. The GLM hosting endpoint exposes a higher output ceiling, but that is a serving limit, not a promise of an answer of that length. For a classification or extraction feature, cap the response around the fields you need. GLM supports low, high and max reasoning effort, defaulting to max; Gemini supports low, medium and high. Map those settings deliberately rather than assuming the same label produces the same amount of work.
GLM offers a separate path to self-hosting
GLM 5.3 Flash has released MIT-licensed weights and documented serving options including vLLM and SGLang. Gemini 3.8 Flash is a hosted model. GLM’s 320 billion total parameters and 18 billion active parameters describe different things: the active count does not mean the full model fits in memory like an 18-billion-parameter checkpoint. If you want control of the deployment, inspect the actual files, precision and framework support before renting GPUs. API token prices cannot tell you the cost of that infrastructure.
Choose around a finished task
For a text extraction feature, start with GLM and check whether it returns the required fields correctly. For audio intake, Gemini can remove a separate processing step. For an existing Gemini application, include the work of changing file handling, tool calls and error recovery before switching. Compare rejected answers, retries and manual corrections alongside token costs. That shows whether a cheaper request also produces a cheaper usable result.
Common questions
Can GLM 5.3 Flash read a PDF directly?
The compared GLM route lists text, image and video inputs, while Gemini also lists file input. For GLM, extract the text or render relevant pages as images with a separate document-processing step. Preserve tables and page references where they matter to the question.
Does Flash mean the two models have the same speed?
No. Flash is part of each model’s name. Response time depends on the model, hosting service, request size and generation settings. This comparison does not include an independent speed test.
Which is better for a long document?
Both have enough context for many large document tasks, but a context limit does not establish answer accuracy. GLM has the lower token bill at the compared rates. Gemini offers direct file input, which may simplify the document workflow. Check whether the result finds and cites the right passages before choosing.