| Signal | Falcon3 7B Instruct | Delta | Mistral Nemo |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 100 | -- | |
Context window size | 65 | -9 | |
Recency | 32 | +28 | |
Output Capacity | 65 | +45 | |
| Overall Result | 2 wins | of 5 | 1 wins |
Score History
40
current score
Falcon3 7B Instruct
right now
39.9
current score
TII
Mistral AI
Falcon3 7B Instruct saves you $3.50/month
That's $42.00/year compared to Mistral Nemo at your current usage level of 100K calls/month.
| Metric | Falcon3 7B Instruct | Mistral Nemo | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | Falcon3 7B Instruct |
| Rank | #295 | #296 | Falcon3 7B Instruct |
| Quality Rank | #295 | #296 | Falcon3 7B Instruct |
| Adoption Rank | #295 | #296 | Falcon3 7B Instruct |
| Parameters | 7B | -- | -- |
| Context Window | 33K | 131K | Mistral Nemo |
| Pricing | Free | $0.02/$0.03/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Falcon3 7B Instruct |
| Pricing | 100 | 100 | Falcon3 7B Instruct |
| Context window size | 65 | 73 | Mistral Nemo |
| Recency | 32 | 4 | Falcon3 7B Instruct |
| Output Capacity | 65 | 20 | Falcon3 7B Instruct |
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 40/100 (rank #295), placing it in the top -1% of all 290 models tracked.
Scores 40/100 (rank #296), placing it in the top -2% 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.
Compare the cost per quality point to find the best value for your specific workload.
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. Falcon3 7B Instruct 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 ($0.00/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
Falcon3 7B Instruct and Mistral Nemo 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.
Best for Quality
Falcon3 7B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Falcon3 7B Instruct
100% lower pricing; better value at scale
Best for Reliability
Falcon3 7B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Falcon3 7B Instruct
Stronger community support and better developer experience
Best for Production
Falcon3 7B Instruct
Wider enterprise adoption and proven at scale
by TII
| Capability | Falcon3 7B Instruct | Mistral Nemo |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
TII
Mistral AI
Falcon3 7B Instruct saves you $0.0720/month
That's 100% cheaper than Mistral Nemo 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 | Falcon3 7B Instruct | Mistral Nemo |
|---|---|---|
| Context Window | 33K | 131K |
| Max Output Tokens | 8,192 | -- |
| Open Source | Yes | Yes |
| Created | Dec 17, 2024 | Jul 19, 2024 |