---
date: 2026-07-09
artifact_type: 5090-share-kit
status: distribution-ready
canonical: https://bmdpat.com/5090-reports
latest_artifact: https://bmdpat.com/5090-reports/latest.md
failure_artifact: https://bmdpat.com/5090-reports/failures/2026-06-12-gemma4-26b.md
email_cta: https://bmdpat.com/5090-reports
linkedin_cta: https://bmdpat.com/5090-reports?utm_source=linkedin&utm_medium=social&utm_campaign=5090-reports&utm_content=share-kit
x_cta: https://bmdpat.com/5090-reports?utm_source=x&utm_medium=social&utm_campaign=5090-reports&utm_content=share-kit
reddit_cta: https://bmdpat.com/5090-reports?utm_source=reddit&utm_medium=social&utm_campaign=5090-reports&utm_content=share-kit
channels:
  - linkedin
  - x
  - r/LocalLLaMA
---

# The 5090 Reports Share Kit - 2026-07-09

Use one draft per post. Keep one artifact and one CTA to the email list.

## Source Artifact

- Hub and email CTA: https://bmdpat.com/5090-reports
- Raw report: https://bmdpat.com/5090-reports/latest.md
- Failure log: https://bmdpat.com/5090-reports/failures/2026-06-12-gemma4-26b.md
- Status: benchmark-live
- Result: Six measured tokens/sec rows on the RTX 5090: llama3.1:8b Q4_K_M holds 207-229 tok/s generation and gemma4:26b Q4_K_M holds 180-207 tok/s, with VRAM, watts, and a 140-second model-reload gotcha documented in the notes.

## LinkedIn Draft

Four weeks ago the first 5090 Reports artifact was a public failure log: gemma4:26b timed out before a single tokens/sec row.

Today the full sweep is live. Six measured rows on the RTX 5090:

llama3.1:8b Q4_K_M: 207-229 tok/s generation, 12k tok/s prompt eval on a 4.3k-token prompt, 7.8 GB peak VRAM.
gemma4:26b Q4_K_M: 180-207 tok/s generation, 20.2 GB peak VRAM.

The useful finding was not the speed. Changing num_ctx between requests silently forced a full model reload. For the 26B that is 140 seconds per swap. Pin your context size in agent stacks.

Raw artifact with method and gotchas: https://bmdpat.com/5090-reports/latest.md

Get the weekly lab notes: https://bmdpat.com/5090-reports?utm_source=linkedin&utm_medium=social&utm_campaign=5090-reports&utm_content=share-kit

## X Draft

1/ The 5090 Reports went from public failure log to six measured rows.

RTX 5090, Ollama 0.31.1, temperature 0, bounded output.

2/ Results:
llama3.1:8b Q4_K_M: 207-229 tok/s gen, 12k tok/s prompt eval, 7.8 GB peak
gemma4:26b Q4_K_M: 180-207 tok/s gen, 20.2 GB peak

3/ The gotcha that matters: changing num_ctx between requests forces a full model reload. 140 seconds per swap on the 26B. Pin your context size.

4/ Cost note: roughly 3 cents of electricity per million output tokens at measured watts.

Raw artifact: https://bmdpat.com/5090-reports/latest.md

Get the weekly lab notes: https://bmdpat.com/5090-reports?utm_source=x&utm_medium=social&utm_campaign=5090-reports&utm_content=share-kit

## r/LocalLLaMA Draft

Title: RTX 5090 + Ollama measured: llama3.1:8b at 207-229 tok/s, gemma4:26b at 180-207 tok/s, and a num_ctx reload gotcha

Body:

Follow-up to my first public run four weeks ago, which was a failure log (gemma4:26b timed out before one valid row). This week the full sweep completed.

Setup: RTX 5090 (32 GB), Ollama 0.31.1, /api/generate, temperature 0, tokens/sec from Ollama's own eval accounting, watts and VRAM sampled from nvidia-smi at 0.5s.

Results across short-gen, long-context summarize (~4.4k tok prompt), and an agent-style code task:

- llama3.1:8b Q4_K_M: 206.7-228.9 tok/s generation, 12,109 tok/s prompt eval, peak 7.8 GB VRAM
- gemma4:26b Q4_K_M: 180.2-207.4 tok/s generation, 6,179 tok/s prompt eval, peak 20.2 GB VRAM

The thing I actually learned: changing num_ctx between requests forces a full model reload every time. On the 26B that is about 140 seconds per swap. If your agent stack varies context size per call, you are paying that constantly. Pin num_ctx.

Also documented: the first prompt-eval reading after load is a cold-start artifact (15 tok/s vs 6,179 on the next request), and why my June failure was a timeout budget problem, not a model problem.

Raw artifact with the full table and method: https://bmdpat.com/5090-reports/latest.md
Original failure log: https://bmdpat.com/5090-reports/failures/2026-06-12-gemma4-26b.md

Future reports and the email list are here: https://bmdpat.com/5090-reports?utm_source=reddit&utm_medium=social&utm_campaign=5090-reports&utm_content=share-kit