DeepSeek V4-Flash vs GLM-5.2
DeepSeek's DeepSeek V4-Flash and Z.ai's GLM-5.2 both target production language workloads, but they price and behave differently. Here is the side-by-side.
Pricing checked against provider documentation on . How we verify
The short answer
DeepSeek V4-Flash is the cheaper option — roughly 6.5x less on a blended workload, and it suits the cheapest capable open-weight option. GLM-5.2 justifies its premium when you need mit-licensed coding agents.
DeepSeek • DeepSeek V4
$0.22 / $0.66
/ 1M tokens (input / output)
A 284B-parameter MoE with only 13B active, which is why it runs fast and prices low. Notable for a 384K maximum output — far beyond the 128K most frontier models cap at — and for supporting both thinking and non-thinking modes, so you can switch reasoning off on easy requests rather than paying for it.
Z.ai • GLM-5
$1.40 / $4.40
/ 1M tokens (input / output)
A 744B-parameter MoE with 40B active, MIT-licensed, and tuned for long-horizon coding work. It sits between DeepSeek and Kimi on price and is the usual challenger when a cheaper model keeps looping or missing repository conventions — enough capability to finish the task without flagship pricing.
Input price
GLM-5.2 is 6.4x the price than DeepSeek V4-Flash on input tokens.
Output price
GLM-5.2 is 6.7x the price than DeepSeek V4-Flash on output tokens — usually the side that dominates the bill.
Monthly cost at three workload sizes
Standard (non-batch, non-cached) rates. Reasoning models will exceed these figures because thinking tokens bill as output.
| Workload | DeepSeek V4-Flash | GLM-5.2 | Difference |
|---|---|---|---|
| Light — 1M in / 200K out | $0 | $2 | $2 |
| Moderate — 10M in / 2M out | $4 | $23 | $19 |
| Heavy — 100M in / 20M out | $35 | $228 | $193 |
Specification comparison
| Attribute | DeepSeek V4-Flash | GLM-5.2 |
|---|---|---|
| Input (/ 1M tokens) | $0.22 | $1.40 |
| Output (/ 1M tokens) | $0.66 | $4.40 |
| Cached input | $0.01 | $0.26 |
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 384,000 tokens | 131,072 tokens |
| Native reasoning | Yes | Yes |
| Knowledge cutoff | 2026-03 | 2026-02 |
| Relative latency | low | medium |
| Open weights | MIT | MIT |
| API model ID | deepseek-v4-flash | glm-5.2 |
| Status | stable | stable |
DeepSeek V4-Flash: Off-peak rate shown. Peak rates double ($0.44 / $1.32) during 01:00–04:00 and 06:00–10:00 UTC on weekdays. Superseded the earlier flat-rate pricing of $0.14 / $0.28 that many comparison sites still quote.
GLM-5.2: Independently measured by Artificial Analysis; the vendor's own pricing page was unreachable at time of checking. Treat as approximate and confirm in the console.
Choose DeepSeek V4-Flash if…
- High-volume classification and extraction
- Very long generated outputs
- Budget coding agents
- Local deployment on modest hardware
Choose GLM-5.2 if…
- Coding agents on large repositories
- Long-horizon refactors
- Self-hosted agent stacks
- Structured output pipelines
Frequently asked
Is DeepSeek V4-Flash or GLM-5.2 cheaper?
DeepSeek V4-Flash is cheaper. On a blended 3:1 input-to-output workload it costs about 6.5x less than GLM-5.2.
Which has the larger context window, DeepSeek V4-Flash or GLM-5.2?
Both accept up to 1M tokens, so context is not a differentiator here.
Should I use DeepSeek V4-Flash or GLM-5.2?
Pick DeepSeek V4-Flash for the cheapest capable open-weight option. Pick GLM-5.2 for mit-licensed coding agents. If cost dominates the decision, DeepSeek V4-Flash wins; if you need the capability ceiling, benchmark both on your own evals before committing.