SSyncDev

AI model comparison

Llama 3.1 405B vs Qwen3 30b A3b Instruct 2507

Compare recorded price, context, output limits, speed, latency, capabilities, and input/output support. Every missing value stays visible, and unsourced benchmarks are excluded.

This Llama 3.1 405B vs Qwen3 30b A3b Instruct 2507 comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Llama 3.1 405B by Meta currently records 128K context, 4.1K maximum output, $3.50 input per 1M tokens, $3.50 output per 1M tokens, 30 t/s recorded output speed, 0.70s recorded time to first token. Qwen3 30b A3b Instruct 2507 by Alibaba via Requesty records 131.1K context, 65.5K maximum output, $0.20 input per 1M tokens, $0.80 output per 1M tokens. The tables below separate documented capabilities, commercial limits, directory measurements, and source-linked benchmark evidence so you can see where the data is complete and where independent testing is still required.

Side-by-sideSpecs and pricing, compared

Meta

Llama 3.1 405B

Meta's largest open-weights model, competitive with frontier closed models.

Context
128K
Max output
4.1K
Input / 1M
$3.50
Output / 1M
$3.50
Output speed
30 t/s

Accepts

  • Text input

Produces

  • Text output
Full model profileVendor docs ↗
VS

Alibaba via Requesty

Qwen3 30b A3b Instruct 2507

Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and agentic tool use. Post-trained on instruction data, it demonstrates competitive performance across reasoning (AIME, ZebraLogic), coding (MultiPL-E, LiveCodeBench), and alignment (IFEval, WritingBench) benchmarks. It outperforms its non-instruct variant on subjective and open-ended tasks while retaining strong factual and coding performance.

Context
131.1K
Max output
65.5K
Input / 1M
$0.20
Output / 1M
$0.80
Output speed
—

Accepts

  • Text input
  • Image input

Produces

  • Text output
Full model profileVendor docs ↗

At a glance

Decision snapshot

This is a directional summary of the values recorded in this directory—not a universal quality verdict. Test the finalists on your own prompts before committing.

Where Llama 3.1 405B leads in recorded data

No complete recorded factor currently favors this model. That does not establish lower real-world quality.

Where Qwen3 30b A3b Instruct 2507 leads in recorded data

  • Context capacity: 131.1K
  • Maximum output: 65.5K
  • Input price: $0.20
  • Output price: $0.80

Context capacity

Higher listed limit

Llama 3.1 405B:128K

Qwen3 30b A3b Instruct 2507:131.1K

Qwen3 30b A3b Instruct 2507

Maximum output

Higher listed limit

Llama 3.1 405B:4.1K

Qwen3 30b A3b Instruct 2507:65.5K

Qwen3 30b A3b Instruct 2507

Input price

Lower recorded price

Llama 3.1 405B:$3.50

Qwen3 30b A3b Instruct 2507:$0.20

Qwen3 30b A3b Instruct 2507

Output price

Lower recorded price

Llama 3.1 405B:$3.50

Qwen3 30b A3b Instruct 2507:$0.80

Qwen3 30b A3b Instruct 2507

Output speed

Higher recorded throughput

Llama 3.1 405B:30 t/s

Qwen3 30b A3b Instruct 2507:—

No complete comparison

Time to first token

Lower recorded latency

Llama 3.1 405B:0.70s

Qwen3 30b A3b Instruct 2507:—

No complete comparison

Intelligence Index

Higher directory index

Llama 3.1 405B:74.0

Qwen3 30b A3b Instruct 2507:—

No complete comparison

Evidence

Verified shared benchmarks

A score appears only when both records include a verified source. It is not treated as a universal ranking.

These two models haven't been measured on the same benchmark yet, so there's nothing meaningful to chart. Comparing scores from different tests would tell you more about the tests than the models — the specs and pricing above are the better guide here.

Specifications

Pricing, limits and capabilities

SpecificationLlama 3.1 405BQwen3 30b A3b Instruct 2507
ProviderMetaAlibaba via Requesty
Model familyLlama 3.1—
Accepted inputstexttext, image
Produced outputstexttext
Context window128K131.1KRecorded lead
Max output4.1K65.5KRecorded lead
Intelligence Index74.0—
Input price / 1M$3.50$0.20Recorded lead
Output price / 1M$3.50$0.80Recorded lead
Output speed30 t/s—
Time to first token0.70s—
Reasoning modeNot documentedNot documented
Tool callingDocumentedDocumented
Image inputNot documentedDocumented
Audio inputNot documentedNot documented
Structured outputDocumentedDocumented
LicenseOpen weightsNot documented
ReleasedJul 23, 2024Not documented

Workload guidance

Which model should you choose?

Llama 3.1 405B has no complete recorded factor that establishes a lead. Qwen3 30b A3b Instruct 2507 currently leads on larger context, larger maximum output, lower recorded input price, lower recorded output price. Choose according to the constraints that matter to your workload, then run the same representative prompts against both models before making a production commitment. Neither the larger number nor the lower price is automatically the better choice: prompt quality, tool reliability, modality support, rate limits, data policy, and provider implementation can change the result. Use this page to build a shortlist, confirm current terms in the linked sources, and validate quality, latency, and cost with your own traffic.

Provenance

Sources and data limits

Prices and hosted performance can change. SyncDev records source references and clearly separates documented specifications from measured values; confirm commercial terms with the provider before deployment.

Questions people ask

It compares recorded context and output limits, token prices, output speed, time to first token, Intelligence Index, modality support, tool and structured-output capabilities, release information, and only source-linked benchmarks verified on both records. Missing information is labeled rather than inferred.

Compare a different pair

Choose any two approved model records and review them with the same evidence rules.

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