SAVRN Model Hub · Comparisons
gpt-oss-20b vs Ornith-1.5-35B-A3B-NVFP4
Gpt-oss-20b has 20.9B parameters and Ornith-1.5-35B-A3B-NVFP4 has 19.5B parameters; gpt-oss-20b is released under Apache License 2.0 and Ornith-1.5-35B-A3B-NVFP4 under MIT License; at 16-bit, gpt-oss-20b needs about 50.2 GB (1x MI300X from $1.85 an hour) and Ornith-1.5-35B-A3B-NVFP4 about 46.9 GB (1x MI300X from $1.85 an hour).
| Field | gpt-oss-20b openai/gpt-oss-20b | Ornith-1.5-35B-A3B-NVFP4 ornith-ai/Ornith-1.5-35B-A3B-NVFP4 |
|---|---|---|
| Publisher | OpenAI | Ornith |
| Task | Text generation | Text generation |
| Modality | Text | Text |
| Parameters, as reported | 20.9B parameters | 19.5B parameters |
| Architecture | GptOssForCausalLM | Qwen3_5MoeForConditionalGeneration |
| Library | transformers | transformers |
| Context length | 131,072 tokens | 262,144 tokens |
| Repository size | 41.3 GB | 23.5 GB |
| Artifact formats | safetensors | safetensors |
| License | apache-2.0 | mit |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 50.2 GB | 46.9 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 12.5 GB | 11.7 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 6cee5e81ee83 | 94e431d9cc47 |
| Downloads reported by the hub | 6M | 1.1M |
| Last observed | 2026-10-16 | 2026-10-16 |
An evaluation row appears only where at least two of these models report the same benchmark with the same stated configuration, metric, unit and setup. Different evaluators stay named in each cell. Values are shown as reported: no unit conversion, no ranking.
Other Reported Results
These results are listed for each model on its own, because the conditions needed to compare them are not stated or do not match. Two results that leave a condition blank are not assumed to share it.
gpt-oss-20b
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| Idavidrein/gpqa | Task diamondMetric diamondSetup GPQA DiamondComparison conditions not established | 58.5859 | EvalEval Reported by a third party |
Evaluated revision not stated | 2026-04-19 |
| Idavidrein/gpqa | Task diamondMetric diamondSetup Reasoning: mediumComparison conditions not established | 66 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| Idavidrein/gpqa | Task diamondMetric diamondSetup Reasoning: high, With toolsComparison conditions not established | 74.2 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| Idavidrein/gpqa | Task diamondMetric diamondSetup Reasoning: highComparison conditions not established | 71.5 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| Idavidrein/gpqa | Task diamondMetric diamondSetup Reasoning: low, With toolsComparison conditions not established | 58 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| Idavidrein/gpqa | Task diamondMetric diamondSetup Reasoning: medium, With toolsComparison conditions not established | 67.1 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| Idavidrein/gpqa | Task diamondMetric diamondSetup Reasoning: lowComparison conditions not established | 56.8 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| LEXam-Benchmark/LEXam | Task mcq_4_choicesMetric mcq_4_choicesComparison conditions not established | 40.78 | LEXam Leaderboard Reported by a third party |
Evaluated revision not stated | 2026-06-02 |
| LEXam-Benchmark/LEXam | Task open_questionMetric open_questionComparison conditions not established | 32.12 | LEXam Leaderboard Reported by a third party |
Evaluated revision not stated | 2026-06-02 |
| LiquidAI/ifstruct-v1.0 | Task ifstruct_v1Metric ifstruct_v1Comparison conditions not established | 91.95 | Liquid AI — IFStruct v1.0 blog (gpt-oss-20b) Reported by a third party |
Evaluated revision not stated | 2026-06-30 |
| SWE-bench/SWE-bench_Verified | Task swe_bench_%_resolvedMetric swe_bench_%_resolvedSetup Reasoning: lowComparison conditions not established | 37.4 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| SWE-bench/SWE-bench_Verified | Task swe_bench_%_resolvedMetric swe_bench_%_resolvedSetup Reasoning: mediumComparison conditions not established | 53.2 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| SWE-bench/SWE-bench_Verified | Task swe_bench_%_resolvedMetric swe_bench_%_resolvedSetup Reasoning: highComparison conditions not established | 60.7 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| TIGER-Lab/MMLU-Pro | Task mmlu_proMetric mmlu_proComparison conditions not established | 73.6 | EvalEval Reported by a third party |
Evaluated revision not stated | 2026-06-30 |
| cais/hle | Task hleMetric hleSetup Reasoning: lowComparison conditions not established | 4.2 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| cais/hle | Task hleMetric hleSetup Reasoning: medium, With toolsComparison conditions not established | 8.8 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| cais/hle | Task hleMetric hleSetup Reasoning: mediumComparison conditions not established | 7 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| cais/hle | Task hleMetric hleSetup Reasoning: highComparison conditions not established | 10.9 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| cais/hle | Task hleMetric hleSetup Reasoning: high, With toolsComparison conditions not established | 17.3 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
| cais/hle | Task hleMetric hleSetup Reasoning: low, With toolsComparison conditions not established | 6.3 | GPT-OSS Model Card Reported by a third party |
Evaluated revision not stated | 2025-08-05 |
SAVRN's Notes on gpt-oss-20b
Five hosts on the SAVRN Index serve gpt-oss-20b by the token, from $0.03 in and $0.14 out per million at DeepInfra to $0.10 and $0.50 at Groq. Owned, this text generator fits on one card: 12.5 GB at 4-bit, 25.1 GB at 8-bit, 50.2 GB at 16-bit, and the least expensive card listed, a 192 GB MI300X, rents for $1.85 an hour, so even full precision leaves room for its 131,072-token context.
You can modify and resell this one; Apache 2.0 allows commercial use, modification and redistribution as long as the notices stay intact. The publisher says it was trained on its harmony response format and should only be used with it, so your serving stack has to speak harmony. And settle rent-or-own yourself: whether $0.14 per million output tokens beats $1.85 an hour depends on how many tokens a day you push through.
SAVRN's Notes on Ornith-1.5-35B-A3B-NVFP4
The name says 35B-A3B, the parameter field says 19.5B, and the published weights are 23.4 GB. All three can be true of a 256-expert mixture with 8 experts active per token, but it means confirming the precision you actually load before sizing hardware. Our table reads 46.9 GB needed at 16-bit, 23.4 GB at 8-bit and 11.7 GB at 4-bit — all fit one MI300X at $1.85 an hour, with the 262,144-token window the real consumer.
Ornith's pitch is process, not benchmarks: a self-improvement loop that generates its own tasks, builds scaffolds and rolls out solutions, refined with reinforcement learning, extending Ornith-1.0 — which the card says was built on Qwen3.5 and Gemma4 with continued pre-training and post-training. MIT makes commercial use open. At 1M downloads a month and with no base-model terms on the page, the homework is confirming upstream obligations yourself.
Questions
Which is larger, gpt-oss-20b or Ornith-1.5-35B-A3B-NVFP4?
gpt-oss-20b (20.9B parameters) is larger than Ornith-1.5-35B-A3B-NVFP4 (19.5B parameters), by the parameter counts their publishers report.
Which is cheaper to run, gpt-oss-20b or Ornith-1.5-35B-A3B-NVFP4?
At 4-bit, gpt-oss-20b fits on 1x MI300X from $1.85 an hour and Ornith-1.5-35B-A3B-NVFP4 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use gpt-oss-20b commercially?
Yes. gpt-oss-20b is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
Can I use Ornith-1.5-35B-A3B-NVFP4 commercially?
Yes. Ornith-1.5-35B-A3B-NVFP4 is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.