Ling 3.0 flash vs MiniMax M2.7
Ling 3.0 flash scores higher on the intelligence index, 25 against 23. The cheapest machine here that runs MiniMax M2.7 is the Mac Studio M5 Ultra, 256GB, at $10,799. Ling 3.0 flash runs on the Framework Desktop, 128GB at $3,449, $7,350 less. On the Mac Studio M5 Ultra, 256GB, the cheapest machine here that runs both, Ling 3.0 flash is about 4.2× quicker: 104 tok/s against 25, both estimated from memory bandwidth. At 500k tokens a day the Mac Studio M5 Ultra, 256GB pays for itself in 272 years running MiniMax M2.7, against 3,706 years running Ling 3.0 flash.
| Ling 3.0 flash | MiniMax M2.7 | |
|---|---|---|
| Intelligence index | 25 | 23 |
| Class | Haiku-class | Haiku-class |
| Weights | 78 GB | 140 GB |
| Needs at 32k | 78 GB | 149 GB |
| Quantisation | Q4_K_M | Q4_K_M |
| Parameters | 124B (5.1B active) | 228.7B (10B active) |
| Max context | 256k | 200k |
| API price per 1M | $0.021 in / $0.063 out | $0.21 in / $0.84 out |
| Licence | MIT | other (see repo) |
| Machines here that run it | 12 of 37 | 1 of 37 |
| Cheapest machine that runs it | Strix Halo Framework Desktop, 128GB $3,449 | Mac Studio M5 Ultra, 256GB $10,799 |
Run Ling 3.0 flash on the Framework Desktop, 128GB · or MiniMax M2.7 on the Mac Studio M5 Ultra, 256GB
Jump to: Side by side on the Mac Studio M5 Ultra, 256GB · 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 Mac Studio M5 Ultra, 256GB
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 Mac Studio M5 Ultra, 256GB is the cheapest machine here that runs both, so this is the pair doing the same work on the same hardware.
| Ling 3.0 flash | MiniMax M2.7 | |
|---|---|---|
| Speed at 32k | 104 tok/s estimated | 25 tok/s estimated |
| Pay-back on this machine | Pays back in 3,706 years | Pays back in 272 years |
| API cost per month | $0.36 | $3.80 |
Run Ling 3.0 flash on the Mac Studio M5 Ultra, 256GB · or MiniMax M2.7
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. MiniMax M2.7 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 | Ling 3.0 flash | MiniMax M2.7 |
|---|---|---|
| 50ka few chats a day | 37,057 years | 2,720 years |
| 200klight assistant use | 9,264 years | 680 years |
| 1Ma moderate coding-assistant day | 1,853 years | 136 years |
| 4Mheavy coding with an agent | 463 years | 34 years |
| 20Magents running most of the day | 93 years | 6.8 years |
Run Ling 3.0 flash at 20M tokens a day · or MiniMax M2.7
Machines that run one and not the other
Ling 3.0 flash needs 78 GB of memory at 32k of context and MiniMax M2.7 needs 149 GB. That puts Ling 3.0 flash on 11 of the 37 machines priced here that MiniMax M2.7 does not, starting at $3,449.
| Machine | Price | Memory | Speed on Ling 3.0 flash | Pay-back |
|---|---|---|---|---|
| Strix Halo Framework Desktop, 128GB | $3,449 | 128 GB | 41 tok/s estimated | Pays back in 1,352 years |
| Strix Halo GMKtec EVO-X2, 128GB | $3,500 | 128 GB | 41 tok/s estimated | Pays back in 1,505 years |
| Strix Halo GMKtec EVO-X3, 128GB | $3,600 | 128 GB | 41 tok/s estimated | Pays back in 1,548 years |
| Strix Halo Minisforum MS-S1 Max, 128GB | $3,799 | 128 GB | 41 tok/s estimated | Pays back in 1,489 years |
| Strix Halo Beelink GTR9 Pro, 128GB | $4,349 | 128 GB | 41 tok/s estimated | Pays back in 1,705 years |
| DGX Spark GB10 Grace Blackwell, 128GB | $4,699 | 128 GB | 51 tok/s estimated | Pays back in 1,717 years |
5 more, on the Ling 3.0 flash page.
Ling 3.0 flash is also head to head with Tencent Hy3 above it on the leaderboard. Two more models need much the same memory: Qwen3.5 122B-A10B and Mistral Small 4 (119B-2603). MiniMax M2.7 is also head to head with Qwen3.6 27B below it on the leaderboard. Two more models need much the same memory: DeepSeek V4-Flash and Qwen3 235B-A22B Instruct 2507.
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 Ling 3.0 flash · every machine that runs MiniMax M2.7 · every other match-up · both against the frontier · the quickest pay-back at each level of use