| Signal | Coder Large | Delta | Virtuoso Large |
|---|---|---|---|
Capabilities | 17 | -17 | |
Pricing | 1 | 0 | |
Context window size | 72 | -9 | |
Recency | 72 | -- | |
Output Capacity | 20 | -60 | |
| Overall Result | 0 wins | of 5 | 4 wins |
11
days higher
2
days
17
days higher
arcee-ai
arcee-ai
Coder Large saves you $45.00/month
That's $540.00/year compared to Virtuoso Large at your current usage level of 100K calls/month.
| Metric | Coder Large | Virtuoso Large | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #238 | #237 | Virtuoso Large |
| Quality Rank | #238 | #237 | Virtuoso Large |
| Adoption Rank | #238 | #237 | Virtuoso Large |
| Parameters | -- | -- | -- |
| Context Window | 33K | 131K | Virtuoso Large |
| Pricing | $0.50/$0.80/M | $0.75/$1.20/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 33 | Virtuoso Large |
| Pricing | 1 | 1 | Virtuoso Large |
| Context window size | 72 | 81 | Virtuoso Large |
| Recency | 72 | 72 | Coder Large |
| Output Capacity | 20 | 80 | Virtuoso Large |
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%). Here's what the scores mean for these two models:
Scores 40/100 (rank #238), placing it in the top 18% of all 290 models tracked.
Scores 40/100 (rank #237), placing it in the top 19% of all 290 models tracked.
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.
Coder Large offers 33% better value per quality point. At 1M tokens/day, you'd spend $19.50/month with Coder Large vs $29.25/month with Virtuoso Large - a $9.75 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. Coder Large also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.80/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content
Coder Large and Virtuoso Large are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Coder Large
Marginally better benchmark scores; both are excellent
Best for Cost
Coder Large
33% lower pricing; better value at scale
Best for Reliability
Coder Large
Higher uptime and faster response speeds
Best for Prototyping
Coder Large
Stronger community support and better developer experience
Best for Production
Coder Large
Wider enterprise adoption and proven at scale
by arcee-ai
| Capability | Coder Large | Virtuoso Large |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
arcee-ai
arcee-ai
Coder Large saves you $0.9300/month
That's 33% cheaper than Virtuoso Large 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 | Coder Large | Virtuoso Large |
|---|---|---|
| Context Window | 33K | 131K |
| Max Output Tokens | -- | 64,000 |
| Open Source | No | No |
| Created | May 5, 2025 | May 5, 2025 |
Both Coder Large and Virtuoso Large score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Coder Large is ranked #238 and Virtuoso Large is ranked #237 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Coder Large is cheaper at $0.80/M output tokens vs Virtuoso Large's $1.20/M output tokens - 1.5x more expensive. Input token pricing: Coder Large at $0.50/M vs Virtuoso Large at $0.75/M.
Virtuoso Large has a larger context window of 131,072 tokens compared to Coder Large's 32,768 tokens. A larger context window means the model can process longer documents and conversations.