SAVRN Model Hub · Comparisons
Meta-Llama-3-8B-Instruct vs Qwen3-8B
Meta-Llama-3-8B-Instruct has 8B parameters and Qwen3-8B has 8.2B parameters; Meta-Llama-3-8B-Instruct is released under Meta Llama 3 Community License and Qwen3-8B under Apache License 2.0; at 16-bit, Meta-Llama-3-8B-Instruct needs about 19.3 GB (1x MI300X from $1.85 an hour) and Qwen3-8B about 19.7 GB (1x MI300X from $1.85 an hour).
| Field | Meta-Llama-3-8B-Instruct meta-llama/Meta-Llama-3-8B-Instruct | Qwen3-8B Qwen/Qwen3-8B |
|---|---|---|
| Publisher | Meta Llama | Qwen |
| Task | Text generation | Text generation |
| Modality | Text | Text |
| Parameters, as reported | 8B parameters | 8.2B parameters |
| Architecture | LlamaForCausalLM | Qwen3ForCausalLM |
| Library | transformers | transformers |
| Context length | Not stated | 40,960 tokens |
| Repository size | 32.1 GB | 16.4 GB |
| Artifact formats | safetensors, pytorch | safetensors |
| License | llama3 | apache-2.0 |
| Access | Access requested at publisher | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 19.3 GB | 19.7 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 4.8 GB | 4.9 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 8afb486c1db2 | b968826d9c46 |
| Downloads reported by the hub | 1.2M | 13M |
| Last observed | 2026-09-18 | 2026-09-18 |
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.
Meta-Llama-3-8B-Instruct
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| TIGER-Lab/MMLU-Pro | Task mmlu_proMetric mmlu_proComparison conditions not established | 40.98 | EvalEval Reported by a third party |
Evaluated revision not stated | 2026-06-30 |
Qwen3-8B
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| LiquidAI/ifstruct-v1.0 | Task ifstruct_v1Metric ifstruct_v1Comparison conditions not established | 79.75 | Liquid AI — IFStruct v1.0 blog (Qwen3-8B) Reported by a third party |
Evaluated revision not stated | 2026-06-30 |
SAVRN's Notes on Meta-Llama-3-8B-Instruct
Nineteen point three gigabytes is the number to plan around at 16-bit, 16.1 of that being weights. At 8-bit the need falls to 9.6 gigabytes; at 4-bit it is 4.8, small enough that the 192 gigabyte MI300X the Index lists as cheapest, at $1.85 an hour, is far more card than one copy needs. That headroom is the point: room to serve many sessions at once.
The Llama 3 Community License permits commercial use with conditions: attribution as Meta specifies, compliance with Meta's Acceptable Use Policy, and a separate license request for any licensee with more than 700 million monthly active users on the release date. Access is gated, so the files arrive only after the publisher approves you. Check the context length, which our record does not carry, and the age of the weights, released April 17, 2024 and last updated June 18, 2025.
SAVRN's Notes on Qwen3-8B
At 16-bit the weights are 16.4 GB and the model needs 19.7 GB, which fits one MI300X with 192 GB, the Index's cheapest setup at $1.85 an hour on-demand. At 8-bit the need drops to 9.8 GB and at 4-bit to 4.9 GB, so the question is never which card but how many copies to stack on one. With 8.2 billion parameters, a 40,960-token context and a switch between thinking and non-thinking modes, this is a text model for everyday work.
The license is the easy part: Apache 2.0 permits commercial use, modification and redistribution, with notices and any NOTICE file kept and significant changes stated, plus an express patent grant. Two things to weigh: it derives from Qwen3-8B-Base, so decide whether you want this checkpoint or the base, and compare the hourly card against the one Index host price, Nscale at $0.07 in and $0.18 out per million tokens.
Questions
Which is larger, Meta-Llama-3-8B-Instruct or Qwen3-8B?
Qwen3-8B (8.2B parameters) is larger than Meta-Llama-3-8B-Instruct (8B parameters), by the parameter counts their publishers report.
Which is cheaper to run, Meta-Llama-3-8B-Instruct or Qwen3-8B?
At 4-bit, Meta-Llama-3-8B-Instruct fits on 1x MI300X from $1.85 an hour and Qwen3-8B on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use Meta-Llama-3-8B-Instruct commercially?
Yes, with conditions. Meta-Llama-3-8B-Instruct is released under Meta Llama 3 Community License. The Llama 3 Community License permits commercial use, except that a licensee whose products had more than 700 million monthly active users on the release date must request a license from Meta. It requires attribution as the license specifies and compliance with Meta's Acceptable Use Policy.
Can I use Qwen3-8B commercially?
Yes. Qwen3-8B 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.