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Granite 4.0 1B

11 tokens a second on Linux · no GPU · 4 CPUs · 31 GB RAM. No hosted API sells it, so this network is the place to run it.

6 builds of Granite 4.0 1B, 7 signed runs on real machines: different packagers, precisions and engines, each a different file with its own numbers.

12tok/s, fastest machine
$2.74per M tokens · no API sells it
4Kcontext proved by recall
1.2 GBmemory, smallest build
2providers measured it
Run it on your gram Install a gram with one command. It works through the catalog on your own machine and signs every result. 2 providers have measured Granite 4.0 1B so far.Use it in your own room Ask Evo in your gramx and it runs on a machine that proved it, at the metered $2.74 per million tokens. On your own machines it costs you nothing.Compare every build Put it beside every other model in one table: speed, price, context and the API price, one row each.
best on ollama · 6 builds

trained 128K · proved 4K context, by ibm-granite Q4_0

11.9 tok/s peak, by ibm-granite Q4_0

Speed against price, every machine

Up and left is faster and cheaper · the line joins machines no other beats on both · price on a log scale

USD per million tokenstok/sLinux · no GPU · 4 CPUs · 31 GB RAM · 4-bit by ibm-granite · 11.37 tok/s · $2.744/MLinux · no GPU · 4 CPUs · 31 GB RAM · 4-bit by ibm-granite · 8.75 tok/s · $3.5635/MLinux · no GPU · 4 CPUs · 31 GB RAM · 3-bit by ibm-granite · 7.98 tok/s · $3.8867/MLinux · no GPU · 4 CPUs · 31 GB RAM · 2-bit by ibm-granite · 7.82 tok/s · $3.9609/MLinux · no GPU · 4 CPUs · 31 GB RAM · 3-bit by ibm-granite · 7.23 tok/s · $4.3044/MLinux · no GPU · 4 CPUs · 31 GB RAM · 16-bit (full precision) by ibm-granite · 4.71 tok/s · $6.9928/M

What it fits on

The smallest build needs about 1.2 GB; 17 of 18 kinds of machine on the network can hold it. Bars: each kind's memory (its card's, else RAM) · ticks: every build, at the size it held plus a fifth for the prompt.

  1. Linux, CPU only · 2 CPUs1 GB RAMnone
  2. NVIDIA GeForce RTX 3050 Laptop GPU4 GB on the card5 of 6
  3. NVIDIA GeForce GTX 16504 GB on the card5 of 6
  4. AMD Radeon(TM) Vega 8 Mobile Graphics7 GB RAMevery build
  5. Windows, CPU only · 12 CPUs7 GB RAMevery build
  6. Apple silicon8 GB RAMevery build
  7. Apple M18 GB RAMevery build
  8. Mac, CPU only · 8 CPUs8 GB RAMevery build
  9. NVIDIA GeForce RTX 3080 Ti12 GB on the cardevery build
  10. Tesla T415 GB on the cardevery build
  11. Intel(R) UHD Graphics 73016 GB RAMevery build
  12. Intel(R) Iris(R) Xe Graphics16 GB RAMevery build
  13. Apple M416 GB RAMevery build
  14. Apple M116 GB RAMevery build
  15. NVIDIA L422 GB on the cardevery build
  16. 2× Tesla T429 GB on the cardevery build
  17. Linux, CPU only · 4 CPUs31 GB RAMevery build
  18. NVIDIA RTX PRO 6000 Blackwell Server Edition95 GB on the cardevery build

How far back it remembers, machine by machine

Filled: the needle came back at that prompt size · outlined: asked and lost · blank: not asked · trained for 128K. 2 walks ended because the model forgot, 5 because the machine could not hold the prompt.

machine · build4K8Kwhy it stopped
Gram ·e61d3b2× Tesla T4 · Q4_0 by ibm-granite4K too slow to answer here
Gram ·e61d3b2× Tesla T4 · Q4_K_M by ibm-granite4K too slow to answer here at 8K
Gram ·acbe75Linux, CPU only · 4 CPUs · Q4_K_M by ibm-granite4K the model lost the needle at 8K
Gram ·e61d3b2× Tesla T4 · Q3_K_S by ibm-granite4K too slow to answer here
Gram ·e61d3b2× Tesla T4 · Q3_K_L by ibm-granite4K too slow to answer here
Gram ·e61d3b2× Tesla T4 · BF16 by ibm-granite4K too slow to answer here at 8K
Gram ·e61d3b2× Tesla T4 · Q2_K by ibm-granite— the model lost the needle at 4K

Carbon per million tokens

Lowest build on each machine · 0 of 2 read off a power sensor, the rest modelled from the parts · fewer grams is better

  1. Gram ·e61d3b238 g4.02 J/tok · modelled
  2. Gram ·acbe75501 g3.81 J/tok · modelled

Carbon is location-based: signed energy × the yearly average of the grid where the machine signed its place (EU grid average (applied to NL) · world grid average (place not signed); Ember Global Electricity Review 2025 (2024 generation), location-based). Facility overhead is not included. A machine on its own solar is not credited until it can prove it.

Measured by

The people whose machines signed these numbers

proved by at least one build: Tool calling · Tool loop finished · Structured output · Sustained output · Writes code · Follows instructions

Every build

Each its own file with its own page: the machines that ran it and their signatures.

buildenginewhose workmemorycontext provedbest tok/smachines
Q4_0 by ibm-granitehf.co/ibm-granite/granite-4.0-1b-GGUF:Q4_0ollamavendor · ibm-granite1.5 GB4K11.91
Q4_K_M by ibm-granitehf.co/ibm-granite/granite-4.0-1b-GGUF:Q4_K_Mollamavendor · ibm-granite1.6 GB4K11.52
Q3_K_S by ibm-granitehf.co/ibm-granite/granite-4.0-1b-GGUF:Q3_K_Sollamavendor · ibm-granite1.3 GB4K8.51
Q3_K_L by ibm-granitehf.co/ibm-granite/granite-4.0-1b-GGUF:Q3_K_Lollamavendor · ibm-granite1.5 GB4K7.21
BF16 by ibm-granitehf.co/ibm-granite/granite-4.0-1b-GGUF:BF16ollamavendor · ibm-granite4.1 GB4K4.71
Q2_K by ibm-granitehf.co/ibm-granite/granite-4.0-1b-GGUF:Q2_Kollamavendor · ibm-granite1.2 GB—8.21
derivatives — somebody else's change to these weights

Fine-tunes, merges and abliterations of this member, each its own model with its own page. None of their numbers are counted above.

Granite-4.0-1B-BE-GGUFnot measuredgranite-4.0-1bnot measured