Compare

Qwen2.5-Coder-32b-Instruct vs Qwen3-Embedding-0.6b

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.

Search2/4
Qwen2.5-Coder-32b-Instruct
qwen/qwen2.5-coder-32b-instruct
Qwen3-Embedding-0.6b
qwen/qwen3-embedding-0.6b
Provider
Alibaba Qwen
Alibaba Qwen
Family
Qwen
Qwen
Modality
text
embedding
Context window
32,768 tok
Max output
32,768 tok
Released
2025-02-27
2025-06-18
License
Open-weight
Open-weight
Input price
$0.660 /1M
$0.012 /1M
Output price
$1.00 /1M
$0.0000 /1M
Tools
yes
Streaming
yes
Vision
JSON mode
yes
Reasoning
Prompt caching
Batch API
Try it
Open in playground →
View model →
Qwen2.5-Coder-32b-Instruct
qwen/qwen2.5-coder-32b-instruct
Full spec →

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-Coder brings the following improvements upon CodeQwen1.5:

Strengths
  • Code-tuned
  • Tool calling
  • Multi-lingual code
Use cases
Code generationRepo-scale Q&ACoding agents
Qwen3-Embedding-0.6b
qwen/qwen3-embedding-0.6b
Full spec →

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks.

Strengths
  • Semantic similarity
  • Vector search
Use cases
RAGSemantic searchRecommendation

Compare with another

Deepseek-R1-Distill-Qwen-32b vs Qwen3-Embedding-0.6b
deepseek/deepseek-r1-distill-qwen-32b · qwen/qwen3-embedding-0.6b
Qwen3-30b-A3b-Fp8 vs Qwen3-Embedding-0.6b
qwen/qwen3-30b-a3b-fp8 · qwen/qwen3-embedding-0.6b
Qwen3-Embedding-0.6b vs Qwq-32b
qwen/qwen3-embedding-0.6b · qwen/qwq-32b
Qwen 3 Max vs Qwen3-Embedding-0.6b
alibaba/qwen3-max · qwen/qwen3-embedding-0.6b
Qwen 3.5 397B A17B vs Qwen3-Embedding-0.6b
alibaba/qwen3.5-397b-a17b · qwen/qwen3-embedding-0.6b
Deepseek-R1-Distill-Qwen-32b vs Qwen2.5-Coder-32b-Instruct
deepseek/deepseek-r1-distill-qwen-32b · qwen/qwen2.5-coder-32b-instruct
Qwen2.5-Coder-32b-Instruct vs Qwen3-30b-A3b-Fp8
qwen/qwen2.5-coder-32b-instruct · qwen/qwen3-30b-a3b-fp8
Qwen2.5-Coder-32b-Instruct vs Qwq-32b
qwen/qwen2.5-coder-32b-instruct · qwen/qwq-32b
Qwen 3 Max vs Qwen2.5-Coder-32b-Instruct
alibaba/qwen3-max · qwen/qwen2.5-coder-32b-instruct
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-...",
)

# Qwen2.5-Coder-32b-Instruct
client.chat.completions.create(
    model="qwen/qwen2.5-coder-32b-instruct",
    messages=[{"role":"user","content":"hello"}],
)

# Qwen3-Embedding-0.6b
client.chat.completions.create(
    model="qwen/qwen3-embedding-0.6b",
    messages=[{"role":"user","content":"hello"}],
)
Get an AIgateway keyRun an eval on these →