Decision support

Qwen3 235B-A22B vs Llama 3.1 Nemotron 70B Instruct

Compare canonical objects directly. The useful dimensions change with the object type, so model and hardware comparisons stay separate.

Benchmark results

Head to head on 1 benchmark both models report

  • Qwen3 235B-A22B1lead
  • Llama 3.1 Nemotron 70B Instruct0leads
  • Arena Text

    Arena rating · Higher is better

    • Qwen3 235B-A22B
      Best1402
      +103 ahead · Arena #164CI 1398 to 1407
    • Llama 3.1 Nemotron 70B Instruct
      1299
      Arena #292CI 1291 to 1307
    Runs and sources
    Qwen3 235B-A22B
    • default1402non-thinking · 95% CI 1398 to 1407 · 37,416 votes
    • default137595% CI 1370 to 1380 · 25,927 votes
    Llama 3.1 Nemotron 70B Instruct
    • default129995% CI 1291 to 1307 · 7,140 votes
  • GPQA diamond

    Best published score · Higher is better

    • Qwen3 235B-A22B
      70.7%
      #108 of 161
    • Llama 3.1 Nemotron 70B Instruct
      Not reported
    Runs and sources
    Qwen3 235B-A22B
    • default70.7%
    Llama 3.1 Nemotron 70B Instruct

    Not reported

Each model's best published result is shown; "Not reported" means no matched evaluation, not a score of zero. Arena and DeepSWE ranks are the leaderboards' own; other ranks are among catalogue models with a score. Results from different harnesses or settings are not directly comparable.

Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.

Arena ratings: Arena (lmarena-ai/leaderboard-dataset), licensed CC BY 4.0. Ratings come from pairwise human votes and are only comparable within one leaderboard; the interval is Arena's 95% confidence interval. Model names are matched to the Vertical Tabs catalog.

Model specifications

Release date
April 28, 2025
April 15, 2025
Context window
131K
128K
Native context
—
—
Max output tokens
16,384
8,192
Knowledge cutoff
2025-04
—
Open weights
Open weights
Open weights
Parameter count
235B
70B

API pricing · USD per 1M tokens

Input
—
—
Output
—
—
Cached input
—
—
Cache write
—
—

Capabilities and modalities

Input modalities
text
text
Output modalities
text
text
Tool calling
Supported
Supported
Reasoning option
Supported
—
Supported options
tools, reasoning, temperature
tools, temperature
Capabilities
—
—

Architecture and availability

Architecture
—
—
Model families
—
—
Tokenizer
—
—
Instruction format
—
—
License
—
—
Providers
0
0
Provider endpoints
0
0
Ollama variants
0
0
Metadata source
ai-research
ai-research

A dash means the field is not reported. Provider-specific performance and pricing may differ.

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