GLM vs Kimi vs DeepSeek: Which Open Model Coding Plan Wins Now?
GLM raised prices, Kimi paused signups, and DeepSeek still has no plan. Here's the current state of open model coding subscriptions.
The short answer
Right now, none of the three big open model labs offer a coding subscription that’s both affordable and available. GLM’s coding plan exists but got a lot more expensive. Kimi’s plan technically exists but Moonshot paused new signups after demand outstripped their GPU capacity. DeepSeek, despite building some of the best value models around, has never offered a coding plan at all and remains API-only. That gap is why aggregator plans bundling all three (plus other open models) under one subscription have started to look like the more practical option for people who actually want to code with these models daily.
TL;DR
- GLM’s coding plan got expensive, moving from roughly $18 up to $72 and $160 a month depending on tier, and it only covers GLM models.
- Kimi’s subscription is paused, not discontinued: Moonshot stopped accepting new signups after K3 launched and maxed out their GPU capacity within about 48 hours.
- DeepSeek has no subscription product, meaning anyone who wants to use DeepSeek V4 for coding is stuck on pay-as-you-go API pricing with their own tooling and caching setup.
- Aggregator plans have emerged to fill the gap, offering credits across dozens of open (and some closed) models for a flat monthly fee, with credit multipliers that vary by model based on the deals negotiated with each provider.
- Credit value differs sharply by model: cheaper models like DeepSeek V4 Flash stretch a fixed credit pool into tens of thousands of requests a month, while pricier reasoning models like Kimi K3 might only yield a couple hundred.
- The harness matters as much as the model: tools built specifically to handle open models’ tool-calling quirks tend to perform noticeably better than general purpose coding agents that were designed around Claude or GPT and had open models bolted on later.
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What happened to GLM’s coding plan?
GLM’s coding plan used to be the standout budget pick for people who wanted a strong open model without paying premium prices. That’s changed. Pricing now sits at roughly three tiers, around $18, $72, and $160 a month, with the lower end available only if you commit to longer billing cycles like quarterly or annual. Monthly billing sits well above where the plan used to be.
The bigger limitation isn’t just price, it’s scope. A GLM coding plan gets you GLM models and nothing else. If you want to try DeepSeek, Kimi, or Qwen for a specific task, you’re paying for a separate subscription or falling back to API credits. For a single-model plan, an $18 to $72 monthly floor puts GLM firmly in the “serious paid tool” category rather than the cheap experimentation tier it used to occupy.
Why is Kimi’s coding plan unavailable?
Kimi K2 and K3 are genuinely strong models, but you currently can’t buy a Kimi coding subscription at any price. After K3 launched, demand for Moonshot’s infrastructure spiked so fast that their GPU capacity maxed out within about 48 hours, and the company paused new subscriptions entirely. This isn’t a pricing problem, it’s a capacity problem. Existing subscribers may still have access, but new users are locked out of the official plan regardless of budget.
That leaves API access as the only direct route to Kimi models, which works but requires the same do-it-yourself setup DeepSeek users are stuck with: your own harness, your own request handling, and no bundled rate limit structure to make budgeting predictable.
Does DeepSeek offer any kind of coding subscription?
No. DeepSeek has never launched a coding plan or subscription product of any kind, despite DeepSeek V4 being widely regarded as one of the best value model families available on pure price-to-performance terms. Everything runs through pay-as-you-go API pricing. That means no rate-limited monthly plan, no bundled credits, and no built-in coding harness. Anyone who wants to use DeepSeek for daily coding work has to bring their own agent framework, manage their own prompt caching, and handle billing manually through token usage.
This is the strangest part of the current market: the cheapest, most capable models per dollar are also the hardest to access in a structured, predictable way.
Why did aggregator coding plans start gaining traction?
The gap left by GLM’s price hikes, Kimi’s paused signups, and DeepSeek’s total absence from the subscription market created an opening. Aggregator plans work by negotiating direct deals with multiple model providers and then reselling access as a single flat-rate subscription, with credits that can be spent across whichever model fits the task.
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One example structures this as a $10 a month plan offering $70 in monthly credits spread across more than 30 open and closed models, including GLM, Kimi, DeepSeek, Qwen, and MiniMax variants. The credit multiplier isn’t uniform. Full $70 credit applies to some models like GLM’s latest release and certain Qwen variants, while others like DeepSeek V4 Flash and a Kimi coding variant get $60 in credits, and newer or pricier models sit lower, in the $20 to $47 range, while provider deals are still being negotiated.
The practical effect is that a single subscription can substitute for what would otherwise require three separate plans, at a fraction of the combined cost, assuming you’re comfortable with credits (rather than a fixed-model allowance) as the unit of value.
Is this actually a better deal than GLM, Kimi, or DeepSeek alone?
On raw math, yes, for anyone who wants access to multiple open models rather than committing to one. GLM’s own entry tier alone costs more per month than a $10 aggregator plan, while only covering GLM. Kimi’s official plan isn’t purchasable at any price right now. DeepSeek has nothing to compare. If your goal is flexibility (switching between models depending on task difficulty and cost) an aggregator plan that spans all of them for less than the price of GLM’s cheapest tier is a straightforward value win.
The caveat is that credit consumption varies wildly by model. Cheap, high-throughput models like DeepSeek V4 Flash can turn a shared credit pool into tens of thousands of requests a month. Pricier reasoning-heavy models like Kimi K3 burn through the same dollar value far faster, sometimes down to a couple hundred requests monthly. Anyone relying heavily on the expensive end of the model list won’t get the same effective multiplier as someone using cheaper models for most of their work.
Another factor worth weighing is the harness itself. Open models tend to fail more often on structured tool calls when run inside coding agents originally designed around Claude or GPT. A harness built specifically to repair malformed tool calls and maintain cache continuity across turns can materially change how usable a model feels day to day, independent of the model’s raw benchmark scores.
What should you actually use for coding right now?
If cost and access matter more than brand loyalty to one lab, a reasonable approach is to treat cheaper, high-throughput models as your default for routine work (file edits, small fixes, boilerplate) and reserve pricier, harder-reasoning models for genuinely difficult problems where the extra cost is justified. This mirrors how many open model users already split their workload across GLM, DeepSeek, and Kimi variants depending on task complexity, rather than committing to a single model for everything.
For teams or individuals already locked into Claude Code or ChatGPT’s paid tiers, those remain solid if you want a single integrated ecosystem and don’t specifically need open model access. But for anyone whose priority is using GLM, Kimi, DeepSeek, or Qwen models specifically, the current landscape of official plans (price hikes, paused signups, no plan at all) makes third-party aggregator access look like the more practical route for now.
Frequently Asked Questions
Why did GLM raise its coding plan prices?
The transcript doesn’t specify Moonshot or Zhipu’s exact reasoning, but the practical effect is that GLM’s coding plan moved from a budget-tier option to pricing that starts around $18 a month and rises to $72 or $160 depending on the billing tier and commitment length.
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Is Kimi’s coding plan gone permanently?
No, it’s paused rather than discontinued. Moonshot stopped accepting new subscriptions after demand for K3 maxed out their GPU capacity within about 48 hours of launch. Existing subscribers may retain access, but new sign-ups aren’t currently possible.
Can I use DeepSeek for coding without a subscription?
Yes, that’s currently the only option. DeepSeek offers no coding plan or subscription product, so all access runs through pay-as-you-go API pricing, which means managing your own coding harness, caching, and billing.
Are aggregator coding plans reliable long term?
They depend on the underlying deals a provider negotiates with each model lab, which can change. Credit multipliers per model aren’t fixed forever, and capacity constraints (like the one that hit Kimi) could affect any provider reselling access to these models.
Which open model gives the best value for coding right now?
Based on current pricing and throughput, cheaper high-volume models like DeepSeek V4 Flash offer the most requests per dollar, while GLM’s latest release is considered one of the stronger overall coding performers among open models, making a mixed approach (cheap model for routine work, stronger model for hard problems) the most practical setup.
