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Command R7B (12-2024) vs SWE-1.5

vs
SWE-1.5

Windsurf

36#410
Signal-by-Signal Comparison
SignalCommand R7B (12-2024)DeltaSWE-1.5
Capabilities
33
-17
50
Benchmarks
38
+38
0
Pricing
100
0
100
Context window size
81
+81
0
Recency
15
-47
62
Output Capacity
58
+38
20
Overall Result
3 wins
of 6
3 wins
It's a tie - both models win 3 signals each

Score History

Score History (32 data points)
Command R7B (12-2024)SWE-1.5
Command R7B (12-2024)

35.8

current score

Leader

SWE-1.5

right now

SWE-1.5

36.1

current score

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

Command R7B (12-2024)

Cohere

Per request$0.000112
Daily$0.38
Monthly$11.25
Annual$135.00

SWE-1.5

Windsurf

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

SWE-1.5 saves you $11.25/month

That's $135.00/year compared to Command R7B (12-2024) at your current usage level of 100K calls/month.

100% cheaper
Choose SWE-1.5 for cost optimization

Command R7B (12-2024) pricing:
Input:$0.04/M tokens
Output:$0.15/M tokens
SWE-1.5 pricing:
Input:$0.00/M tokens
Output:$0.00/M tokens
Command R7B (12-2024)

Cohere

36

Composite Score

Winner
SWE-1.5

Windsurf

36

Composite Score

Signal-by-Signal Comparison
MetricCommand R7B (12-2024)SWE-1.5Winner
Overall Score
36
36
SWE-1.5
Rank#411#410
SWE-1.5
Quality Rank#411#410
SWE-1.5
Adoption Rank#411#410
SWE-1.5
Parameters7B----
Context Window128K----
Pricing$0.04/$0.15/MFree--
Signal Scores
Capabilities
33
50
SWE-1.5
Benchmarks
38
--
Command R7B (12-2024)
Pricing
100
100
SWE-1.5
Context window size
81
0
Command R7B (12-2024)
Recency
15
62
SWE-1.5
Output Capacity
58
20
Command R7B (12-2024)
Benchmark Head-to-Head(3 benchmarks)
Command R7B: 0SWE-1.5: 0
Command R7B
SWE-1.5
Normalized 0-100%
MMLU-Pro
28.58%-
IFEval
77.13%-
BBH
36.02%-
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.

Command R7B (12-2024)Entry Level

Scores 36/100 (rank #411), placing it in the top -41% of all 290 models tracked.

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

Scores 36/100 (rank #410), placing it in the top -41% 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 Command R7B (12-2024) when you need:

  • Processing long documents or large codebases (128K token context)

Choose SWE-1.5 when you need:

  • High-volume production workloads where API costs must be minimized
  • Agentic applications using tool/function calling
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Command R7B (12-2024)
Input cost$0.04/M tokens
Output cost$0.15/M tokens
Cost per quality point$0.005
Est. monthly (1M tokens/day)$2.81
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
Command R7B (12-2024)Faster
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

Command R7B (12-2024)

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

Command R7B (12-2024)

Long document analysis

Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass

Command R7B (12-2024)

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 (36/100) correlates with better nuance, coherence, and style in long-form content

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

Command R7B (12-2024) and SWE-1.5 are extremely close in overall performance (only 0.30000000000000426 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by Cohere

  • 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
CapabilityCommand R7B (12-2024)SWE-1.5
Vision (Image Input)
Function Callingdiffers
Streaming
JSON Modediffers
Reasoningdiffers
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Command R7B (12-2024)

Cohere

$0.2475
estimated monthly cost

SWE-1.5

Windsurf

Best Value
$0.000000
estimated monthly cost

SWE-1.5 saves you $0.2475/month

That's 100% cheaper than Command R7B (12-2024) 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
ParameterCommand R7B (12-2024)SWE-1.5
Context Window128K--
Max Output Tokens4,000--
Open SourceNoNo
CreatedDec 14, 2024Sep 1, 2025
Last updated: 12m ago

相关对比

Command R7B (12-2024) vs SWE-1.5 (2026) | LM Market Cap