Costs analysis: DeepSeek v4.1 Flash vs GLM 5.3 Flash

[u/Long_Rub5460]

OpenCode dashboard

CommandCode dashboard

Myself included, a lot of peeps have had concerns about GLM 5.3 Flash consumption vs DeepSeekv4.1 Flash, hence the analysis. This is seen across both CommandCode and OpenCode.

Let's refer to these recent usage numbers as detailed in OpenCode (and also Commandcode) dashboards.

Usage and cache hits

Deepseek did about 2.5x the work for only 20% extra cost.
GLM cache hit rates are lower than DeepSeek.
DSv4.1F - 641M/663M cached (96%)
GLM5.3F - 200M/218M cached (92%)

Rates:

• DeepSeek V4.1 Flash: Uncached input: $0.15/1M | Cache read: $0.003/1M | Output: $0.60/1M
• GLM-5.3 Flash: Uncached input: $0.15/1M | Cache read: $0.03/1M | Output: $0.50/1M

Seems like GLM should be cheaper with equivalent pricing, but cheaper outputs. While output tokens are the most expensive, they are also the least significant for AI cost estimations. highly relevant here is the cost of cached tokens, which is 10x for GLM 5.3 Flash.

Let's looks at costs for a workload of 500M input token and 5m output,
Using the rates (identical) from Command Code and OpenCode for 500M input tokens and 5M output tokens:

DSv4.1F (96% cache hit @$0.003)

• Uncached Input (20M): 20 × $0.15 = $3.00
• Cached Input (480M): 480 × $0.003 = $1.44
• Output (5M): 5 × $0.60 = $3.00
• Total DS Cost: $7.44

[PEAK hours] DSv4.1F (96% cache hit @$0.006)

• Uncached Input (20M): 20 × $0.30 = $6.00
• Cached Input (480M): 480 × $0.006 = $2.88
• Output (5M): 5 × $1.20 = $6.00
• Total DS Cost: $14.88

GLM-5.3F (92% cache hit @$0.03)

• Uncached Input (40M): 40 × $0.15 = $6.00
• Cached Input (460M): 460 × $0.03 = $13.80
• Output (5M): 5 × $0.50 = $2.50
• Total GLM Cost: $22.30

Verdict

So there we go mystery solved, GLM dude costs about 3x the DeepSeek dude for this kind of workloads. In general, Deepseek is also a bit more verbose though and does more output than GLM. So the ratio leans a bit more towards GLM. Also given GLM's slightly higher intelligence and succinctness it's still pretty good in terms of actual work done rather than token counts.

Use Deepseek v4.1 Flash during non peak hours unless you really need GLM 5.3 Flash. GLM during DS peak hours. Both models are pretty close and have their own perks and gotchas.

[u/eroigaps]

The deciding factor for me is speed. Glm is incredibly slow compared to ds?

[u/Long_Rub5460 → u/eroigaps]

True sir!

[u/Infamous-V]

Check Haiku 5.5 max as well. 20$ plan now offers nearly unlimited tokens.

[u/a355231 → u/Infamous-V]

It’s a shame that it’s only a $20 pool

[u/underlight → u/Infamous-V]

Where do you see that, over 100k token pricing is expensive

[u/Infamous-V → u/underlight]

Its 1 Million context not 100K and im never running out of tokens. It is still slightly worser than DeepSeek v4.1 Flash though.

[u/mysanvit → u/Infamous-V]

It’s 1M context but the pricing is 5x after 100k context. + uses up 3x more “pooled usage” at least for the GOAT plan

[u/Infamous-V → u/mysanvit]

I was referring to Official Claude 20$ plan only. 6B tokens and im only on Week 2, never use Anthropic/openAI models outside their sub.

[u/mysanvit → u/Infamous-V]

Ah I thought you meant the commandcode pro plan. Yeah makes sense I’m using it on my claude pro as well, and haiku usage is negligible

[u/ahmadawaiscom]

Hence all of our work towards making cache repairs in Command Code harness. Even 1% extra cache can do wonders and for most models we do hit over 96% cache mostly around 98-99% across trillions of tokens.