Compare

Pareto vs Qwen3.8-27b

Pricing per million tokens, context window, capabilities — pulled from each provider's public docs. All 2 are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.

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P
Pareto
unbiased/pareto
Qwen3.8-27b
qwen/qwen3.8-27b
Provider
Unbiased
Alibaba Qwen
Family
Qwen
Modality
text
text
Context window
262,144 tok
262,144 tok
Max output
32,768 tok
32,768 tok
Released
2026-09-17
2026-08-17
License
Open-weight
Open-weight
Input price
$2.50 /1M
$0.450 /1M
Output price
$7.50 /1M
$3.20 /1M
Tools
yes
Streaming
yes
yes
Vision
yes
JSON mode
yes
Reasoning
yes
Prompt caching
Batch API
Try it
Open in playground →
Open in playground →
Pareto
unbiased/pareto
Full spec →

Pareto is Unbiased's blended AI model. It engages multiple language models in parallel for each request, synthesizes one answer, and supports text and vision inputs through a single API response.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
Use cases
ChatbotsContent generationAgentic workflows
Qwen3.8-27b
qwen/qwen3.8-27b
Full spec →

Qwen 3.8 27B is a 27-billion-parameter instruction-tuned language model from Alibaba's Qwen family, designed for vision, efficient general-purpose text generation and agentic workloads.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
Use cases
ChatbotsContent generationAgentic workflows

Compare with another

GPT-6 Astra vs Pareto
openai/gpt-6-astra · unbiased/pareto
GPT-6 Astra vs Qwen3.8-27b
openai/gpt-6-astra · qwen/qwen3.8-27b
Claude Fable 5.1 vs Pareto
anthropic/claude-fable-5.1 · unbiased/pareto
Claude Fable 5.1 vs Qwen3.8-27b
anthropic/claude-fable-5.1 · qwen/qwen3.8-27b
Claude Opus 5 vs Pareto
anthropic/claude-opus-5 · unbiased/pareto
Claude Opus 5 vs Qwen3.8-27b
anthropic/claude-opus-5 · qwen/qwen3.8-27b
Gemini 3.8 Flash vs Pareto
google/gemini-3.8-flash · unbiased/pareto
Gemini 3.8 Flash vs Qwen3.8-27b
google/gemini-3.8-flash · qwen/qwen3.8-27b
Glm-5.3 vs Pareto
zai-org/glm-5.3 · unbiased/pareto
SWITCH BETWEEN THEM

One key, all 2, one line different.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.aigateway.sh/v1",
    api_key="sk-aig-...",
)

# Pareto
client.chat.completions.create(
    model="unbiased/pareto",
    messages=[{"role":"user","content":"hello"}],
)

# Qwen3.8-27b
client.chat.completions.create(
    model="qwen/qwen3.8-27b",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyRun an eval on these →