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GPT-3.5 Turbo (batch) vs Qwen2.5 Coder 32B Instruct

Signal-by-Signal Comparison
SignalGPT-3.5 Turbo (batch)DeltaQwen2.5 Coder 32B Instruct
Capabilities
67
+50
17
Pricing
99
+0
99
Context window size
67
-5
72
Recency
0
-17
17
Output Capacity
60
-15
75
Overall Result
2 wins
of 5
3 wins
Qwen2.5 Coder 32B Instruct wins 3 of 5 signals

Score History

Score History (25 data points)
GPT-3.5 Turbo (batch)Qwen2.5 Coder 32B Instruct
GPT-3.5 Turbo (batch)

40

current score

Leader

GPT-3.5 Turbo (batch)

right now

Qwen2.5 Coder 32B Instruct

39.3

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

GPT-3.5 Turbo (batch)

OpenAI

Best Value
Per request$0.000625
Daily$2.08
Monthly$62.50
Annual$750.00

Qwen2.5 Coder 32B Instruct

Alibaba

Per request$0.001160
Daily$3.87
Monthly$116.00
Annual$1392.00

GPT-3.5 Turbo (batch) saves you $53.50/month

That's $642.00/year compared to Qwen2.5 Coder 32B Instruct at your current usage level of 100K calls/month.

46% cheaper
Choose GPT-3.5 Turbo (batch) for cost optimization

GPT-3.5 Turbo (batch) pricing:
Input:$0.25/M tokens
Output:$0.75/M tokens
Qwen2.5 Coder 32B Instruct pricing:
Input:$0.66/M tokens
Output:$1.00/M tokens
Winner
GPT-3.5 Turbo (batch)

OpenAI

40

Composite Score

Qwen2.5 Coder 32B Instruct

Alibaba

39

Composite Score

Signal-by-Signal Comparison
MetricGPT-3.5 Turbo (batch)Qwen2.5 Coder 32B InstructWinner
Overall Score
40
39
GPT-3.5 Turbo (batch)
Rank#363#364
GPT-3.5 Turbo (batch)
Quality Rank#363#364
GPT-3.5 Turbo (batch)
Adoption Rank#363#364
GPT-3.5 Turbo (batch)
Parameters--32B--
Context Window16K33K
Qwen2.5 Coder 32B Instruct
Pricing$0.25/$0.75/M$0.66/$1.00/M--
Signal Scores
Capabilities
67
17
GPT-3.5 Turbo (batch)
Pricing
99
99
GPT-3.5 Turbo (batch)
Context window size
67
72
Qwen2.5 Coder 32B Instruct
Recency
0
17
Qwen2.5 Coder 32B Instruct
Output Capacity
60
75
Qwen2.5 Coder 32B Instruct
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

GPT-3.5 Turbo (batch)Entry Level

Scores 40/100 (rank #363), placing it in the top -25% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen2.5 Coder 32B InstructEntry Level

Scores 39/100 (rank #364), placing it in the top -25% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose GPT-3.5 Turbo (batch) when you need:

  • Agentic applications using tool/function calling

Choose Qwen2.5 Coder 32B Instruct when you need:

  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
GPT-3.5 Turbo (batch)Best Value
Input cost$0.25/M tokens
Output cost$0.75/M tokens
Cost per quality point$0.025
Est. monthly (1M tokens/day)$15.00
Qwen2.5 Coder 32B Instruct
Input cost$0.66/M tokens
Output cost$1.00/M tokens
Cost per quality point$0.042
Est. monthly (1M tokens/day)$24.90

GPT-3.5 Turbo (batch) offers 40% better value per quality point. At 1M tokens/day, you'd spend $15.00/month with GPT-3.5 Turbo (batch) vs $24.90/month with Qwen2.5 Coder 32B Instruct - a $9.90 monthly difference.

Latency & Speed
GPT-3.5 Turbo (batch)Faster
Speed score0/100
Qwen2.5 Coder 32B Instruct
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

GPT-3.5 Turbo (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. GPT-3.5 Turbo (batch) also offers lower per-token costs for high-volume support

GPT-3.5 Turbo (batch)

Long document analysis

Larger context window (33K tokens) can process longer documents, contracts, and research papers in a single pass

Qwen2.5 Coder 32B Instruct

Batch data extraction

Lower output pricing ($0.75/M) reduces costs when processing thousands of records daily

GPT-3.5 Turbo (batch)

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

GPT-3.5 Turbo (batch)
Which Should You Choose?
Our recommendation:
GPT-3.5 Turbo (batch)

GPT-3.5 Turbo (batch) and Qwen2.5 Coder 32B Instruct are extremely close in overall performance (only 0.7000000000000028 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 40% lower pricing; better value at scale
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Alibaba

Consider for specialized use cases.

Capability Comparison
CapabilityGPT-3.5 Turbo (batch)Qwen2.5 Coder 32B Instruct
Vision (Image Input)
Function Callingdiffers
Streaming
JSON Modediffers
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-3.5 Turbo (batch)

OpenAI

Best Value
$1.35
estimated monthly cost

Qwen2.5 Coder 32B Instruct

Alibaba

$2.39
estimated monthly cost

GPT-3.5 Turbo (batch) saves you $1.04/month

That's 43% cheaper than Qwen2.5 Coder 32B Instruct at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGPT-3.5 Turbo (batch)Qwen2.5 Coder 32B Instruct
Context Window16K33K
Max Output Tokens4,09632,768
Open SourceNoYes
CreatedMay 28, 2023Nov 11, 2024
Last updated: 35m ago

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GPT-3.5 Turbo (batch) vs Qwen2.5 Coder 32B Instruct (2026) | LM Market Cap