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Qwen2.5 7B Instruct vs SWE-1.5

Qwen2.5 7B Instruct

Alibaba

38#366
vs
SWE-1.5

Windsurf

38#365
Signal-by-Signal Comparison
SignalQwen2.5 7B InstructDeltaSWE-1.5
Capabilities
50
--
50
Benchmarks
39
+39
0
Pricing
100
0
100
Context window size
72
+72
0
Recency
12
-58
71
Output Capacity
75
+55
20
Overall Result
3 wins
of 6
2 wins
Qwen2.5 7B Instruct wins 3 of 6 signals

Score History

Score History (25 data points)
Qwen2.5 7B InstructSWE-1.5
Qwen2.5 7B Instruct

38.1

current score

Leader

SWE-1.5

right now

SWE-1.5

38.2

current score

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

Qwen2.5 7B Instruct

Alibaba

Per request$0.000200
Daily$0.67
Monthly$20.00
Annual$240.00

SWE-1.5

Windsurf

Best Value
Per request$0.000000
Daily$0.00
Monthly$0.00
Annual$0.00

SWE-1.5 saves you $20.00/month

That's $240.00/year compared to Qwen2.5 7B Instruct at your current usage level of 100K calls/month.

100% cheaper
Choose SWE-1.5 for cost optimization

Qwen2.5 7B Instruct pricing:
Input:$0.10/M tokens
Output:$0.20/M tokens
SWE-1.5 pricing:
Input:$0.00/M tokens
Output:$0.00/M tokens
Qwen2.5 7B Instruct

Alibaba

38

Composite Score

Winner
SWE-1.5

Windsurf

38

Composite Score

Signal-by-Signal Comparison
MetricQwen2.5 7B InstructSWE-1.5Winner
Overall Score
38
38
SWE-1.5
Rank#366#365
SWE-1.5
Quality Rank#366#365
SWE-1.5
Adoption Rank#366#365
SWE-1.5
Parameters7B----
Context Window33K----
Pricing$0.10/$0.20/MFree--
Signal Scores
Capabilities
50
50
Qwen2.5 7B Instruct
Benchmarks
39
--
Qwen2.5 7B Instruct
Pricing
100
100
SWE-1.5
Context window size
72
0
Qwen2.5 7B Instruct
Recency
12
71
SWE-1.5
Output Capacity
75
20
Qwen2.5 7B Instruct
Benchmark Head-to-Head(4 benchmarks)
Qwen2.5 7B: 0SWE-1.5: 0
Qwen2.5 7B
SWE-1.5
Normalized 0-100%
MMLU-Pro
36.52%-
IFEval
75.85%-
BBH
34.89%-
BigCodeBench
37.6%-
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.

Qwen2.5 7B InstructEntry Level

Scores 38/100 (rank #366), placing it in the top -26% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
SWE-1.5Entry Level

Scores 38/100 (rank #365), placing it in the top -26% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-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 Qwen2.5 7B Instruct when you need:

  • Self-hosted deployments where you need full control over the model

Choose SWE-1.5 when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Qwen2.5 7B Instruct
Input cost$0.10/M tokens
Output cost$0.20/M tokens
Cost per quality point$0.008
Est. monthly (1M tokens/day)$4.50
SWE-1.5
Input cost$0.00/M tokens
Output cost$0.00/M tokens
Cost per quality point$0.000
Est. monthly (1M tokens/day)$0.00

Both models are priced similarly, so the decision comes down to quality and features rather than cost.

Latency & Speed
Qwen2.5 7B InstructFaster
Speed score0/100
SWE-1.5
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

Qwen2.5 7B Instruct

Customer support chatbot

Suitable for user-facing chat with competitive response times. SWE-1.5 also offers lower per-token costs for high-volume support

Qwen2.5 7B Instruct

Long document analysis

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

Qwen2.5 7B Instruct

Batch data extraction

Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily

SWE-1.5

Creative writing & content

Higher overall composite score (38/100) correlates with better nuance, coherence, and style in long-form content

SWE-1.5
Which Should You Choose?
Our recommendation:
SWE-1.5

Qwen2.5 7B Instruct and SWE-1.5 are extremely close in overall performance (only 0.10000000000000142 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by Alibaba

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • 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
SWE-1.5
Recommended

by Windsurf

  • Choose for Cost - 100% lower pricing; better value at scale
Capability Comparison
CapabilityQwen2.5 7B InstructSWE-1.5
Vision (Image Input)
Function Calling
Streaming
JSON Modediffers
Reasoningdiffers
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Qwen2.5 7B Instruct

Alibaba

$0.4200
estimated monthly cost

SWE-1.5

Windsurf

Best Value
$0.000000
estimated monthly cost

SWE-1.5 saves you $0.4200/month

That's 100% cheaper than Qwen2.5 7B 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
ParameterQwen2.5 7B InstructSWE-1.5
Context Window33K--
Max Output Tokens32,768--
Open SourceYesNo
CreatedOct 16, 2024Sep 1, 2025
Last updated: 37m ago

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