| Signal | Mercury 2 | Delta | Kimi K2.5 |
|---|---|---|---|
Capabilities | 67 | -17 | |
Pricing | 1 | -1 | |
Context window size | 81 | -5 | |
Recency | 100 | -- | |
Output Capacity | 78 | -2 | |
| Overall Result | 0 wins | of 5 | 4 wins |
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Inception
Moonshot AI
Mercury 2 saves you $92.50/month
That's $1110.00/year compared to Kimi K2.5 at your current usage level of 100K calls/month.
| Metric | Mercury 2 | Kimi K2.5 | Winner |
|---|---|---|---|
| Overall Score | 78 | 87 | Kimi K2.5 |
| Rank | #84 | #46 | Kimi K2.5 |
| Quality Rank | #84 | #46 | Kimi K2.5 |
| Adoption Rank | #84 | #46 | Kimi K2.5 |
| Parameters | -- | -- | -- |
| Context Window | 128K | 262K | Kimi K2.5 |
| Pricing | $0.25/$0.75/M | $0.45/$2.20/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 83 | Kimi K2.5 |
| Pricing | 1 | 2 | Kimi K2.5 |
| Context window size | 81 | 86 | Kimi K2.5 |
| Recency | 100 | 100 | Mercury 2 |
| Output Capacity | 78 | 80 | Kimi K2.5 |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 78/100 (rank #84), placing it in the top 71% of all 290 models tracked.
Scores 87/100 (rank #46), placing it in the top 84% of all 290 models tracked.
Kimi K2.5 has a 9-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Mercury 2 offers 62% better value per quality point. At 1M tokens/day, you'd spend $15.00/month with Mercury 2 vs $39.75/month with Kimi K2.5 — a $24.75 monthly difference.
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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Mercury 2 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.75/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (87/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input — can analyze screenshots, diagrams, photos, and scanned documents directly
Kimi K2.5 has a moderate advantage with a 8.700000000000003-point lead in composite score. It wins on more signal dimensions, but Mercury 2 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Mercury 2
Marginally better benchmark scores; both are excellent
Best for Cost
Mercury 2
62% lower pricing; better value at scale
Best for Reliability
Mercury 2
Higher uptime and faster response speeds
Best for Prototyping
Mercury 2
Stronger community support and better developer experience
Best for Production
Mercury 2
Wider enterprise adoption and proven at scale
by Inception
| Capability | Mercury 2 | Kimi K2.5 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Inception
Moonshot AI
Mercury 2 saves you $2.10/month
That's 61% cheaper than Kimi K2.5 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 | Mercury 2 | Kimi K2.5 |
|---|---|---|
| Context Window | 128K | 262K |
| Max Output Tokens | 50,000 | 65,535 |
| Open Source | Yes | Yes |
| Created | Mar 4, 2026 | Jan 27, 2026 |
Kimi K2.5 scores 87/100 (rank #46) compared to Mercury 2's 78/100 (rank #84), giving it a 9-point advantage. Kimi K2.5 is the stronger overall choice, though Mercury 2 may excel in specific areas like cost efficiency.
Mercury 2 is ranked #84 and Kimi K2.5 is ranked #46 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Mercury 2 is cheaper at $0.75/M output tokens vs Kimi K2.5's $2.20/M output tokens — 2.9x more expensive. Input token pricing: Mercury 2 at $0.25/M vs Kimi K2.5 at $0.45/M.
Kimi K2.5 has a larger context window of 262,144 tokens compared to Mercury 2's 128,000 tokens. A larger context window means the model can process longer documents and conversations.