Sunk Cost sunkcost.ai Data checked 2026-09-03

GLM-5.3-Flash vs Tencent Hy3

GLM-5.3-Flash scores higher on the intelligence index, 42 against 26. No machine on this list runs Tencent Hy3 at 32k of context. GLM-5.3-Flash runs on the Mac Studio M5 Ultra, 256GB, from $10,799. At 500k tokens a day that machine pays for itself in 965 years running GLM-5.3-Flash. Shorten the context to 16k and that machine holds both.

GLM-5.3-FlashTencent Hy3
Intelligence index4226
ClassSonnet-classHaiku-class
Weights189 GB182 GB
Needs at 32k190 GB193 GB
QuantisationUD-Q4_K_MQ4_K_M
Parameters321.3B (18B active)295B (21B active)
Max context1024k256k
API price per 1M$0.075 in / $0.25 out$0.083 in / $0.33 out
LicenceMITApache 2.0
Machines here that run it1 of 370 of 37
Cheapest machine that runs itMac Studio M5 Ultra, 256GB $10,799none listed
Summarising not rated not rated
Translation not rated not rated
Everyday coding not rated not rated
Reasoning & maths not rated not rated
Agentic work not rated not rated

Run GLM-5.3-Flash on the Mac Studio M5 Ultra, 256GB · or Tencent Hy3 at 16k of context

Ratings are coarse on purpose: they say what a model is usable for, not where it places to the decimal.

Side by side on the Mac Studio M5 Ultra, 256GB at 16k of context

Tencent Hy3 needs 193 GB at 32k of context. The biggest machine on this list is the Mac Studio M5 Ultra, 256GB, and it has 192 GB usable. Tencent Hy3's weights are 182 GB of that. The rest is the cache, and the cache is the part that shrinks when you ask for less context: at 16k the model needs 188 GB, which that machine holds. It already runs GLM-5.3-Flash, so at 16k of context one machine here runs both. It costs $10,799. The rest of this page is what each model does with it.

GLM-5.3-FlashTencent Hy3
Speed at 16k33 tok/s estimated20 tok/s estimated
Pay-back on this machinePays back in 955 yearsPays back in 1,022 years
API cost per month$1.31$1.50

Run GLM-5.3-Flash on the Mac Studio M5 Ultra, 256GB · or Tencent Hy3

How much use it takes to pay for the machine

Everything above is at 500k tokens a day. Pay-back moves with how much you actually run, so here are both models at the five levels of use the calculator names, on the Mac Studio M5 Ultra, 256GB at 16k of context. GLM-5.3-Flash pays for it sooner at every level of use, so which of them to run does not turn on how hard you work it.

A day's useGLM-5.3-FlashTencent Hy3
50ka few chats a day9,555 years10,222 years
200klight assistant use2,389 years2,555 years
1Ma moderate coding-assistant day478 years511 years
4Mheavy coding with an agent119 years128 years
20Magents running most of the day24 years26 years

Run GLM-5.3-Flash at 20M tokens a day · or Tencent Hy3

Machines that run one and not the other

GLM-5.3-Flash needs 190 GB of memory at 32k of context and Tencent Hy3 needs 193 GB. That puts GLM-5.3-Flash on 1 of the 37 machines priced here that Tencent Hy3 does not, starting at $10,799.

MachinePriceMemorySpeed on GLM-5.3-FlashPay-back
Mac Studio M5 Ultra, 256GB$10,799256 GB32 tok/s estimatedPays back in 965 years

GLM-5.3-Flash is also head to head with Qwen3.8 Flash Next below it on the leaderboard. Tencent Hy3 is also head to head with Inkling Small above it on the leaderboard and Ling 3.0 flash below it.

The assumptions behind both columns

Both columns use the same usage: 500k tokens a day at 15:1 input to output, 32k of context, $0.17 per kWh, and today's API prices held flat. The two sections that need one machine to hold both models are at 16k of context instead, which is the longest on the calculator's list where one does. Speeds marked estimated are worked out from memory bandwidth rather than measured, and pay-back scales with them. Where nobody rents an open model by the token, its API prices are the nearest hosted model's, named beside them. Machines are the 37 here with a published price that are still sold. Change any of it in the calculator.

More head to head: every machine that runs GLM-5.3-Flash · what Tencent Hy3 needs · every other match-up · both against the frontier · the quickest pay-back at each level of use