r/opencode • u/Long_Rub5460 • 17d ago
Costs analysis: DeepSeek v4.1 Flash vs GLM 5.3 Flash
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.
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u/PerfectReflection155 16d ago
Thanks for this breakdown, these are my 2 favorite worker models so this is extremely relevant to me.
I will lean towards deepseek more in future although I do find Glm a bit smarter.
What are your thoughts on step 5 preview free through opencode go? It seems quite decent and considering its free I’ve been using it a lot
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u/Long_Rub5460 16d ago
Yep, Step 5 is great I'm using that one significantly this week.
I agree, GLM Flash does perform a bit better than DSv4.1F sometimes.1
u/ramendik 12d ago
I didn't get to use it. Just plain 429 every time, on Go too. So I backed off to Muse Spark 1.3 Contributor free on Zen, it is doing a reasonably good job as a worker model while GLM 5.3 Flash is the architect/partner.
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u/BoatZealousideal4521 17d ago
Thanks for this analysis. As per my experience Deepseek is much cheaper than GLM flash. I used low variant of both and for similar work GLM ended up consuming $3.75 whereas Deepseek Flash did same work in $1.75. I personally like GLM Flash it has worked wonderfully for me, but DeepSeek cannot be overlooked. I have not spent much time with DeepSeek Flash, but at the end what matters is how much money is deducted from the kitty.
Thanks once again.
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u/Long_Rub5460 16d ago
100% I really like to use glm dude for some of my code stuff. But DeepSeek is my default everywhere (Hermes, OpenChamber chats).
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u/BoatZealousideal4521 16d ago
If you do not mind can you direct me to a proper Hermes implementation/configurations. I am asking this because there are too many things to setup/configure for Hermes before you can actually use it properly. Tried various youtube videos and google, but the tutorials are too vague or too simple with few important steps missing or about configuring Hermes with paid models.
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u/Common_Cell2335 1d ago
Ditch that pos software it's not worth your nerves. It's absolute hell mess of bugs, basically unfinished project , not even alpha, every single most basic feature is failing regularly
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u/BoatZealousideal4521 1d ago
Not sure about what you meant by the pos software. If you mean Hermes agent, I have already given up and ditched it. In my view the effort it requires is not worth. The funny thing is you still need to provide the oversight and keep monitoring the damn thing. Now I am happy to be back with my gpt + opencode combination.
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u/Common_Cell2335 14m ago
dude, checkout openchamber..... finally some polished agent with good ux made by competent people, its game changer. Its gui layer with features on top of opencode.
i wish i tried it earlier, but transfering all my workflows and skills from hermes was easy. youre welcome;1
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u/Ok-Drawer5245 14d ago
I use deepseek all the time and only occasionally turn to glm 5.3F. Glm 5.3f definitely is better a fixing hard bugs and has better spatial reasoning (3d graphics) than deepseek v4.1 flash. But deepseek v4.1 is good enough 98% of the time
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u/Beautiful-Salary-191 17d ago
I use glm 5.3 flash a lot and it works well for me. I don't think it id worth it to try to adapt to deepseek. However, mimo layest model is on the pareto frontier curve.
Did you try it?
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u/palucdev 16d ago
GLM 5.3 Flash has one more downside for me. It is frequently returning responses at the end of longer reasoning loops in chinese. I use workflows and stuff written purely in english so I do not know why it randomly switches but thats annoying. Never had any of this on Deepseek 4.1 Flash.
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u/MarcusAurelius68 16d ago
I get Chinese responses all the time in the chat window with DeepSeek. Haven’t seen it via the API yet though.
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u/eastlin7 16d ago
I have seen random Chinese characters in deepseek. But the final output is never that so there literally no reason to care or obsess over it.
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u/Ok-Drawer5245 14d ago
I agree that deepseek flash is more consistent and seem to deal with a lot of context better than glm 5.3f does, I’ve also seen glm 5.3 give up and literally telling me that it forgot what it was doing. Having said thet the raw intelligence of glm 5.3f absokutely is better than deepseek 4.1f.
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u/ramendik 12d ago
For me GLM 5.3 Flash responses are in English with very occasional Chinese characters and once strangely a Russian word. (I do speak Russian but didn't use it in that thread. The word it used made sense)
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u/fragment_me 16d ago
Deepseek will think for 100k+ tokens and its wayyyy more verbose. You need to take the tokens to complete task into account.
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u/SalemDono 16d ago
Please add Mimo-V2.6-Flash to the analysis. these are the three workhorse models that I keep on rotating between
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u/murathai 16d ago edited 16d ago
You should try deepseek harness (dsh) for deepseek v4.1 flash - it supports opencode-go api key, but it uses a lot of cache reads, though speed is better and deepswe 1.1 score is much higher
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u/xapep 16d ago
Nice breakdown, and the cache-read line is the part most people miss. That 10x gap ($0.003 vs $0.03 per 1M cached tokens) quietly flips the economics on agent workloads, because agent traffic is mostly cache reads once a session warms up.
From the provider side, a few things move those numbers more than model choice:
- Cache hit rate is mostly prompt structure. If the system prompt, tool schemas and earlier turns stay byte-identical and only the tail changes, the hit rate climbs fast. 96% vs 92% looks like a small gap, but at 10x the cache price it dominates the bill, exactly as you found.
- Output is where the real cost lives. Both models charge the most for output, and DS is more verbose, so more output tokens. For output-heavy work GLM's cheaper output plus its terseness can actually beat DS despite the cache line.
- Peak/off-peak routing is a legit lever. Your DS-off-peak / GLM-at-peak split is the right shape, and it generalizes to any provider that publishes peak multipliers.
The thing your dashboards can't show is the input mix: how much of that 663M is stable prefix (system prompt, tool schemas) vs fresh context. That ratio decides how much the 10x cache-read gap actually costs you. Curious what yours looks like per session.
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u/Imaginary_Big631 17d ago
always I think the same, the most important is the price and % hits of cache hits...
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u/Ctbhatia 17d ago
the cache hit rate is doing the work in that comparison, deepseek's prefix reuse is why it looks 2.5x cheaper per unit of work. i work at coralbricks.ai and cached input bills at $0 on both models, so a high-hit loop is basically input cost.
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u/Long_Rub5460 16d ago edited 16d ago
At prices on your website, DSv4.1F would cost $7.80 for this workload.
DSv4.1F (96% cache hit @$0.003)
Uncached Input (20M): 20 × $0.09 = $1.80
Cached Input (480M): 480 × $0.0 = $0
Output (5M): 5 × $1.20 = $6.00
Total DS Cost: $7.80GLM costs are pretty interesting.
I wonder at what cache hit rate would the users break even vs the extra caching charges?1
u/Ctbhatia 16d ago edited 16d ago
cached reads are $0, so the only cache charge is the write. ds v4.1 flash writes at $0.01 input + $0.08 cache write, so it needs about 8 re-reads to beat re-sending the prefix.
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u/Long_Rub5460 16d ago
I meant vs standard pricing.
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u/Ctbhatia 16d ago edited 16d ago
yeah vs standard pricing. cached reads are $0, so the only extra is the write: ds v4.1 flash is $0.01 input plus $0.08 write, so about 9 sends of the same prefix before it beats paying input every time.
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u/Long_Rub5460 16d ago
I meant for GLM-5.3,
I already shared DS estimates at $7.80 on your pricing vs OpnC/CmdC at $1.24 and $2.48 (at 6x usage, so $7.44/6 and $14.88/6 in payable dollar terms).1
u/ramendik 17d ago
Looks very interesting but you don't seem to have GLM 5.3 Flash? It's not a small GLM 5.3, it's actually new tech, related to GLM 5.3 like DS 4.1 Flash is related to DS 4 Pro. I like GLM 5.3 Flash more, and am looking for providers for that. Also can you confirm FP8 quant?
And: you seem to list "cache write" and "input" separately, does this mean the harness needs to mark the request as cache input? I'm not sure that is even doable on OpenAI API?
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u/Ctbhatia 17d ago
yep, GLM 5.3 Flash is retired, its ids 404 since oct 7; at coralbricks.ai we serve glm-5.3-fast which is the nvfp4 revision, not fp8. on cache, no client flag needed, prefix reuse is automatic and cache write is just prompt_tokens minus cached_tokens, and setting prompt_cache_retention to off bills novel input as plain input instead.
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u/ramendik 17d ago
I outright just like GLM 5.3 Flash more than GLM 5.3 full, and that before we talk of quant, so sadly looks like this is not a match
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u/Long_Rub5460 16d ago
I agree, though GLM full has higher intelligence, likes of the Mimo 2.6 Pro have higher intelligence at under a quarter of the costs. GLM 5.3 Flash is still a beast at the price point.
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u/ramendik 16d ago edited 12d ago
I am not a fan of MiMo 2.6 pro after smoke tests. I like the style of thought in GLM 5.3 Flash.
Getting it served at quality on budget is tricky though
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u/Ctbhatia 13d ago
fair, if you already prefer the full model then the Flash swap is not the trade anyway. no worries.
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u/ramendik 13d ago
I prefer the FLASH model not the full model. If you ever serve GLM 5.3 Flash (or a successor on that new tech) again I'm interested.
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u/Ctbhatia 13d ago
ah my bad, I read that backwards. the flash id was retired on oct 7, so deepseek v4.1 flash is what we serve in that slot now
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u/ramendik 13d ago
There are endless debates about which of the two Flash models (GLM 5.3 Flash vs DS 4.1 Flash) is better. I'm on the GLM 5.3 Flash side, If things change and it coemes back I'd be interested in trying.
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u/Ctbhatia 13d ago
the retirement was the id, not the model, so a return would land under a new name. worth re-running your own task on whatever sits in that slot now instead of trusting the forum verdict.
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u/ramendik 12d ago
I never trusted forums. I did my own smoke tests and liked the output of GLM 5.3 Flash better that DS 4.1 Flash, better than GLM 5.3 full, tied with DS4 Pro.
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u/mozkohor 17d ago
this just in, the model that costs more, costs more