GLM-4.7-Flash vs Gemma 4 12B
GLM-4.7-Flash scores higher on the intelligence index, 15 against 14. The cheapest machine here that runs GLM-4.7-Flash is the Framework Desktop, 32GB, at $1,269. Gemma 4 12B runs on the Mac mini M6, 16GB at $899, $370 less. On the Framework Desktop, 32GB, the cheapest machine here that runs both, GLM-4.7-Flash is about 1.7× quicker: 40 tok/s against 24, both estimated from memory bandwidth. At 500k tokens a day the Framework Desktop, 32GB pays for itself in 97 years running GLM-4.7-Flash, against 104 years running Gemma 4 12B.
| GLM-4.7-Flash | Gemma 4 12B | |
|---|---|---|
| Intelligence index | 15 | 14 |
| Class | Haiku-class | Below every hosted tier |
| Weights | 18 GB | 7.1 GB |
| Needs at 32k | 20 GB | 8.0 GB |
| Quantisation | Q4_K_M | Q4_K_M |
| Parameters | 31.2B (3B active) | 12B |
| Max context | 198k | 256k |
| API price per 1M | $0.0605 in / $0.4 out | $0.08 in / $0.13 outpriced as Qwen3.5 9B |
| Licence | MIT | Apache 2.0 |
| Machines here that run it | 30 of 37 | 37 of 37 |
| Cheapest machine that runs it | Strix Halo Framework Desktop, 32GB $1,269 | Mac mini M6, 16GB $899 |
Run GLM-4.7-Flash on the Framework Desktop, 32GB · or Gemma 4 12B on the Mac mini M6, 16GB
Jump to: Side by side on the Framework Desktop, 32GB · How much use it takes to pay for the machine · Machines that run one and not the other · The assumptions behind both columns
Side by side on the Framework Desktop, 32GB
The table above gives each model the cheapest machine that runs it, and those are two different machines, so nothing in it is a like-for-like race. The Strix Halo Framework Desktop, 32GB is the cheapest machine here that runs both, so this is the pair doing the same work on the same hardware.
| GLM-4.7-Flash | Gemma 4 12B | |
|---|---|---|
| Speed at 32k | 40 tok/s estimated | 24 tok/s estimated |
| Pay-back on this machine | Pays back in 97 years | Pays back in 104 years |
| API cost per month | $1.24 | $1.27priced as Qwen3.5 9B |
Run GLM-4.7-Flash on the Framework Desktop, 32GB · or Gemma 4 12B
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 Framework Desktop, 32GB. GLM-4.7-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 use | GLM-4.7-Flash | Gemma 4 12B |
|---|---|---|
| 50ka few chats a day | 967 years | 1,040 years |
| 200klight assistant use | 242 years | 260 years |
| 1Ma moderate coding-assistant day | 48 years | 52 years |
| 4Mheavy coding with an agent | 12 years | 13 years |
| 20Magents running most of the day | 2.4 years | 2.6 years |
Run GLM-4.7-Flash at 20M tokens a day · or Gemma 4 12B
Machines that run one and not the other
Gemma 4 12B needs 8.0 GB of memory at 32k of context and GLM-4.7-Flash needs 20 GB. That puts Gemma 4 12B on 7 of the 37 machines priced here that GLM-4.7-Flash does not, starting at $899.
| Machine | Price | Memory | Speed on Gemma 4 12B | Pay-back |
|---|---|---|---|---|
| Mac mini M6, 16GB | $899 | 16 GB | 14 tok/s estimated | Pays back in 71 years |
| Mac mini M6, 24GB | $1,099 | 24 GB | 16 tok/s estimated | Pays back in 85 years |
| MacBook Air M5 (13-inch), 16GB | $1,299 | 16 GB | 14 tok/s estimated | Pays back in 102 years |
| MacBook Air M5 (15-inch), 16GB | $1,499 | 16 GB | 14 tok/s estimated | Pays back in 118 years |
| Mac mini M5 Pro, 24GB | $1,699 | 24 GB | 29 tok/s estimated | Pays back in 135 years |
| MacBook Pro M5 (14-inch), 16GB | $1,999 | 16 GB | 14 tok/s estimated | Pays back in 157 years |
1 more, on the Gemma 4 12B page.
GLM-4.7-Flash is also head to head with Granite 4.2 30B above it on the leaderboard. One more model needs much the same memory: Devstral Small 2 24B. Gemma 4 12B is also head to head with Qwen3.5 9B below it on the leaderboard and Gemma 3 12B it, the last-generation Gemma nearest it in size.
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. 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-4.7-Flash · every machine that runs Gemma 4 12B · every other match-up · both against the frontier · the quickest pay-back at each level of use