| Signal | DeepSeek V4 Pro | Delta | Gemma 2 27B |
|---|---|---|---|
Capabilities | 67 | +33 | |
Benchmarks | 75 | -8 | |
Pricing | 99 | 0 | |
Context window size | 96 | +33 | |
Recency | 100 | +88 | |
Output Capacity | 93 | +38 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
75.7
current score
Gemma 2 27B
right now
77.4
current score
DeepSeek
DeepSeek V4 Pro saves you $10.50/month
That's $126.00/year compared to Gemma 2 27B at your current usage level of 100K calls/month.
| Metric | DeepSeek V4 Pro | Gemma 2 27B | Winner |
|---|---|---|---|
| Overall Score | 76 | 77 | Gemma 2 27B |
| Rank | #62 | #54 | Gemma 2 27B |
| Quality Rank | #62 | #54 | Gemma 2 27B |
| Adoption Rank | #62 | #54 | Gemma 2 27B |
| Parameters | -- | 27B | -- |
| Context Window | 1049K | 8K | DeepSeek V4 Pro |
| Pricing | $0.43/$0.87/M | $0.65/$0.65/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 33 | DeepSeek V4 Pro |
| Benchmarks | 75 | 83 | Gemma 2 27B |
| Pricing | 99 | 99 | Gemma 2 27B |
| Context window size | 96 | 62 | DeepSeek V4 Pro |
| Recency | 100 | 12 | DeepSeek V4 Pro |
| Output Capacity | 93 | 55 | DeepSeek V4 Pro |
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.
Scores 76/100 (rank #62), placing it in the top 79% of all 290 models tracked.
Scores 77/100 (rank #54), placing it in the top 82% of all 290 models tracked.
With only a 2-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.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Gemma 2 27B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.65/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (77/100) correlates with better nuance, coherence, and style in long-form content
DeepSeek V4 Pro and Gemma 2 27B are extremely close in overall performance (only 1.7000000000000028 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
DeepSeek V4 Pro
Marginally better benchmark scores; both are excellent
Best for Cost
Gemma 2 27B
0% lower pricing; better value at scale
Best for Reliability
DeepSeek V4 Pro
Higher uptime and faster response speeds
Best for Prototyping
DeepSeek V4 Pro
Stronger community support and better developer experience
Best for Production
DeepSeek V4 Pro
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | DeepSeek V4 Pro | Gemma 2 27B |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
DeepSeek V4 Pro saves you $0.1230/month
That's 6% cheaper than Gemma 2 27B 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.
| Parameter | DeepSeek V4 Pro | Gemma 2 27B |
|---|---|---|
| Context Window | 1.0M | 8K |
| Max Output Tokens | 384,000 | 2,048 |
| Open Source | Yes | Yes |
| Created | Apr 24, 2026 | Jul 13, 2024 |