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Opencode said they are working on matching the old prices using their own inference. Right now, they give 4100 credits for Luna and 63 000 for Deepseek on their prepaid plan (both are 2x)
As well as the headline in/out changes, people heavily using agentic coding tools will want to note the 6x (off peak) and 12x (peak) increase to cache hit pricing on Pro (since cache hit can easily make up 90%+ of input on long sessions). DeepSeek was hugely underpricing cache hit pricing before and even after this increase they're still cheaper on that metric than every other provider I'm aware of, but it will put a…
I think that Flash is still a usable model but Pro is DOA... Even before the price difference between Flash and Pro, vs the intelligence / problem solving / tool calling did not make sense. But now that gap has widen even more. And there are just too many competitors models now close to that Pro price range.
Especially when we compare that competitive models offer subscription services that easily cut down the token price by 1:10. That makes Pro especially a bad value.
We shall see what the 3th party market is going to do, but i suspect that prices will be increased. If the argument was that DeepSeek increases price as they lack capacity, a company with access to billions, other 3th party providers that need to rent and have less optimized infrastructures will increase prices. Especially if they get hit hard with people moving around.
Its like we always see the same issue with popular models.
* GLM 5.2 is good, capacity issues, API price up, subscription heavy nerfs. * Kimi K3 is good, capacity issues, API price up, subscription heavy nerfs. * DeepSeek V4 GA is good, capacity issues, API price up * OpenAI GLM 5m, 10m active users. Subscription usage is sneakily tightened more and more. * Anthropic Opus too popular, ...
That is the main issue. The AI users are people who actively easily move between companies. Pushing peak loads to each unprepared company, releasing load on the "less desired". And round we go ...
According to their post: (Input / Output / Cache Read, [$/M]) DeepSeek-V4-Flash: Prev: 0.14 / 0.28 / 0.0028 Off-Peak: 0.22 (1.6x) / 0.66 (2.4x) / 0.007 (2.5x) Peak: 0.44 (3.1x) / 1.32 (4.7x) / 0.014 (5.0x) DeepSeek-V4-Pro: Prev: 0.435 / 0.87 / 0.003625 Off-Peak: 0.66 (1.5x) / 1.98 (2.3x) / 0.022 (6.1x) Peak: 1.32 (3.0x) / 3.96 (4.6x) / 0.044 (12.1x) gpt-5.6-luna: $0.20 / $1.20 / $0.02 / $0.25 (In / Out / Cache Read /…
> EDIT: formatting Keep at it, I believe in you.
p.s. Thanks DSv4-Flash, for your hard work of converting a messy table into plain text.
Opencode said they are working on matching the old prices using their own inference. Right now, they give 4100 credits for Luna and 63 000 for Deepseek on their prepaid plan (both are 2x)
Do they just set a super low caching time and hope that drops effective cache rates low enough? Do all other providers somehow overcharge by that much? Are they just going to sell it as a loss leader?
About 3x increase. Luna is now a much better deal. Hope they don't increase their prices in response.
Opencode said they are working on matching the old prices using their own inference. Right now, they give 4100 credits for Luna and 63 000 for Deepseek on their prepaid plan (both are 2x)
I doubt they will match old cache read pricing- that’s most important in agentic coding.
Opencode said they are working on matching the old prices using their own inference. Right now, they give 4100 credits for Luna and 63 000 for Deepseek on their prepaid plan (both are 2x)
How could that possibly work? Deepseek was undercutting every other provider by an order of magnitude on cached tokens. Do they just set a super low caching time and hope that drops effective cache rates low enough? Do all other providers somehow overcharge by that much? Are they just going to sell it as a loss leader?
This, I think. Cached inputs have an opportunity cost (keeping the KV cache until use) but a hit is basically free. “Basically” - if the cache is offloaded to system RAM or NVMe there’s some scheduling overhead.
From a consumer viewpoint a more interesting metric than the raw costs is
cached cost * hitrate + input cost * (1 - hitrate)