LLM pricing briefing: March 23, 2026
Weekly LLM pricing update covering GLM 5 at $1.11/M, MiniMax M2.7 at $0.52/M, GPT-5.4 Mini, and open-weight momentum.
The cheapest models worth using keep getting cheaper. This week, the sub-$2/M tier gained real quality contenders, and the premium tier is starting to look hard to justify for most workloads.
The value tier is no longer a compromise
MiniMax M2.7 (MiniMax) sits at $0.52/M input tokens with a 49.6 quality index. MiniMax M2.7 scores within striking distance of GPT-5.2 (51.3 quality) at roughly one-ninth the price. The 43 tok/s inference speed is the trade-off — batch-heavy workloads won't mind, but interactive use will feel sluggish.
Z.ai: GLM 5 (Z AI) lands at $1.11/M with 49.8 quality and 89 tok/s. GLM 5 is open source, which matters for self-hosting economics. At that quality-to-price ratio, it's the strongest open-source option on the board right now.
OpenAI: GPT-5.4 Mini (OpenAI) at $1.69/M delivers 48.1 quality and a blistering 237 tok/s. GPT-5.4 Mini is the speed leader by a wide margin — nearly double the next fastest model in this set. For latency-sensitive applications where you need fast iteration, nothing else comes close.
| Model | Quality | Price/1M | Speed |
|---|---|---|---|
| MiniMax M2.7 | 49.6 | $0.52 | 43 tok/s |
| GLM 5 | 49.8 | $1.11 | 89 tok/s |
| GPT-5.4 Mini | 48.1 | $1.69 | 237 tok/s |
| GPT-5.4 | 57.2 | $5.63 | 85 tok/s |
| Claude Opus 4.6 | 53.0 | $10.00 | 51 tok/s |
Premium models: tied at the top, split on price
Gemini 3.1 Pro Preview (Google) and GPT-5.4 (OpenAI) share an identical 57.2 quality index. Google undercuts OpenAI by $1.13/M ($4.50 vs. $5.63) and runs faster at 117 tok/s versus 85 tok/s. For general-purpose premium work, Gemini 3.1 Pro is the better deal on both axes.
Anthropic's adaptive reasoning models remain the most expensive options at $10.00/M. Claude Opus 4.6 hits 53.0 quality — 4 points below the leaders. That's a tough sell at nearly double the price unless your workflow specifically benefits from Anthropic's reasoning approach.
Community signal: open weights accelerating
The biggest community story this week is MiniMax confirming M2.7 will go open-weight (555 upvotes on r/LocalLLaMA). Combined with Alibaba reaffirming ongoing open-source releases for Qwen and Wan, the self-hosting ecosystem is pulling in competitive models fast. Multiple threads show users running Qwen 3.5 variants on consumer hardware, including V100s hitting 115 tok/s on Qwen Coder 30B.
What to do with this
If you're running batch inference or retrieval pipelines, MiniMax M2.7 at $0.52/M is hard to beat. For interactive applications where latency matters, GPT-5.4 Mini at 237 tok/s is the pick. Premium users should benchmark Gemini 3.1 Pro against GPT-5.4 before defaulting to OpenAI — same quality, lower cost.
Find the right model for your workload constraints with the LLM Selector, or browse current pricing on Explore.
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