Flaxon 0.3.0 and Teloce-Py 0.3.0 are available on PyPI. Release instructions are maintained on this site; source links identify the framework snapshot. Check version and upgrade guidance.
HTTP benchmark results
Measured on 2026-10-09 UTC. These are local HTTP microbenchmarks, not a developer-productivity study.
Environment
- python: 3.12.14 (main, Aug 25 2026, 14:00:49) [Clang 22.1.3 ]
- node: v24.19.0
- go: go version go1.27.2 linux/amd64
- flaxon: 0.2.7
- uvicorn: 0.54.0
- uvloop: 0.23.0
- httptools: 0.8.0
- os: Linux-6.18.44-x86_64-with-glibc2.39
- cpu_model: AMD EPYC 9V74 80-Core Processor
- cpu_quota: 800000 100000
- affinity: [0, 1]
- git_revision: ac4ec523010f1d625e0ca78ece7c63b0423167cf
- flaxon_distribution_metadata: 0.2.6
- flaxon_source: /workspace/scratch/67da7b153f3e/flaxon-orm/src/flaxon/init.py
Method
One server worker pinned to one CPU; client pinned to another. 32 persistent connections, no pipelining. One-second warmup, three five-second samples per endpoint/runtime, randomized order. Plaintext bytes and JSON values were checked on every response. Flaxon uses Uvicorn with uvloop and httptools. Node uses core HTTP; Go uses net/http with GOMAXPROCS=1. No database, TLS, authentication, Admin, CMS, or optional middleware.
| Endpoint | Server | Median requests/s | Sample range | Median run p95 (ms) | Invalid responses |
|---|---|---|---|---|---|
| /plaintext | Flaxon | 14,291 | 11,828–15,210 | 3.319 | 0 |
| /plaintext | Node.js | 65,768 | 65,001–67,357 | 0.881 | 0 |
| /plaintext | Go | 90,614 | 87,406–92,102 | 0.797 | 0 |
| /json | Flaxon | 12,548 | 11,913–13,947 | 3.689 | 0 |
| /json | Node.js | 60,786 | 56,856–60,836 | 0.935 | 0 |
| /json | Go | 78,974 | 78,632–95,499 | 0.864 | 0 |
Throughput differences
- /plaintext: Flaxon processed 21.7% of Node.js's request rate (78.3% lower throughput); Node.js was 4.60× as fast by this measure.
- /plaintext: Flaxon processed 15.8% of Go's request rate (84.2% lower throughput); Go was 6.34× as fast by this measure.
- /json: Flaxon processed 20.6% of Node.js's request rate (79.4% lower throughput); Node.js was 4.84× as fast by this measure.
- /json: Flaxon processed 15.9% of Go's request rate (84.1% lower throughput); Go was 6.29× as fast by this measure.
CPU and limitations
- Flaxon: client CPU 23.4–27.3% of one core; server CPU including startup/warmup 100.4–101.7% of one core.
- Node.js: client CPU 61.8–68.1% of one core; server CPU including startup/warmup 98.4–99.6% of one core.
- Go: client CPU 77.0–80.5% of one core; server CPU including startup/warmup 95.7–96.6% of one core.
Server CPU includes startup and warmup, so it can exceed 100% when normalized only over warmup plus measured duration. Client CPU is measured during the sample, with small startup overhead. This is a shared virtual machine; repeats are short. Closed-loop latency does not represent behavior under a fixed overloaded arrival rate. The client shares the host and faster servers may approach its capacity. Results should be repeated on dedicated hardware, with longer runs and a separate load machine, before making public performance claims.
The measured endpoints do not justify claiming Flaxon is on par with Node.js or Go. Application-level results may differ when databases and other I/O dominate.
Development improvement and fewer bugs
Development time reduction: unmeasured. Developer defect reduction: unmeasured. No human development study was conducted, and neither percentage can be inferred from HTTP throughput, generated code, or passing tests.
Observed HTTP response failure rate is 0% if all samples have zero errors; this describes these benchmark requests only. It is not evidence of a 0% developer defect rate or of fewer bugs than another framework.
See README.md for a controlled study design and separate time-reduction, throughput-improvement, and defect-reduction formulas.
Raw per-run data: results.json. Reproduce with run.py.