ALLaM 7B Instruct (preview) vs SWE-1.5
| Signal | ALLaM 7B Instruct (preview) | Delta | SWE-1.5 |
|---|---|---|---|
Capabilities | 17 | -33 | |
Pricing | 100 | -- | |
Context window size | 57 | +57 | |
Recency | 34 | -36 | |
Output Capacity | 60 | +40 | |
| Overall Result | 2 wins | of 5 | 2 wins |
Score History
37.7
current score
SWE-1.5
right now
38.2
current score
ALLaM 7B Instruct (preview)
HUMAIN
SWE-1.5
Windsurf
| Metric | ALLaM 7B Instruct (preview) | SWE-1.5 | Winner |
|---|---|---|---|
| Overall Score | 38 | 38 | SWE-1.5 |
| Rank | #367 | #365 | SWE-1.5 |
| Quality Rank | #367 | #365 | SWE-1.5 |
| Adoption Rank | #367 | #365 | SWE-1.5 |
| Parameters | 7B | -- | -- |
| Context Window | 4K | -- | -- |
| Pricing | Free | Free | -- |
| Signal Scores | |||
| Capabilities | 17 | 50 | SWE-1.5 |
| Pricing | 100 | 100 | ALLaM 7B Instruct (preview) |
| Context window size | 57 | 0 | ALLaM 7B Instruct (preview) |
| Recency | 34 | 71 | SWE-1.5 |
| Output Capacity | 60 | 20 | ALLaM 7B Instruct (preview) |
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 38/100 (rank #367), placing it in the top -26% of all 290 models tracked.
Scores 38/100 (rank #365), placing it in the top -26% of all 290 models tracked.
With only a 1-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.
Choose ALLaM 7B Instruct (preview) when you need:
- Self-hosted deployments where you need full control over the model
Choose SWE-1.5 when you need:
- Agentic applications using tool/function calling
- Step-by-step reasoning and chain-of-thought problem solving
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. ALLaM 7B Instruct (preview) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (4K 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 (38/100) correlates with better nuance, coherence, and style in long-form content
ALLaM 7B Instruct (preview) and SWE-1.5 are extremely close in overall performance (only 0.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
By Use Case
Best for Quality
ALLaM 7B Instruct (preview)
Marginally better benchmark scores; both are excellent
Best for Cost
ALLaM 7B Instruct (preview)
0% lower pricing; better value at scale
Best for Reliability
ALLaM 7B Instruct (preview)
Higher uptime and faster response speeds
Best for Prototyping
ALLaM 7B Instruct (preview)
Stronger community support and better developer experience
Best for Production
ALLaM 7B Instruct (preview)
Wider enterprise adoption and proven at scale
by HUMAIN
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Cost - 0% lower pricing; better value at scale
- 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
| Capability | ALLaM 7B Instruct (preview) | SWE-1.5 |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
ALLaM 7B Instruct (preview)
HUMAIN
SWE-1.5
Windsurf
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | ALLaM 7B Instruct (preview) | SWE-1.5 |
|---|---|---|
| Context Window | 4K | -- |
| Max Output Tokens | 4,096 | -- |
| Open Source | Yes | No |
| Created | Feb 13, 2025 | Sep 1, 2025 |