ALLaM-2-7b vs o1-pro vs Sonar Deep Research
o1-pro comes out ahead, 55 to 16 and 0 on our weighted score, though Sonar Deep Research is 75× cheaper per token.
SDAIA
ALLaM-2-7b
0/100- ECI—
- Price—
- Context4K
- Our pick
OpenAIo1-pro
55/100- ECI—
- Price$150.00 / $600.00
- Context200K
PerplexitySonar Deep Research
16/100- ECI—
- Price$2.00 / $8.00
- Context128K
o1-pro is our pick
o1-pro is the better all-round choice, scoring 55/100 against Sonar Deep Research (16) and ALLaM-2-7b (0). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceSonar Deep ResearchSonar Deep Research $3.50 · o1-pro $262.50 per 1M tokens (3:1 blend) · ALLaM-2-7b unpriced
- Longest contexto1-proo1-pro 200,000 · Sonar Deep Research 128,000 · ALLaM-2-7b 4,096 tokens
- Widest inputso1-proALLaM-2-7b: Text · o1-pro: Text, Images · Sonar Deep Research: Text
- Self-hostingALLaM-2-7bPublishes downloadable weights
| Measure | Weight | ALLaM-2-7b | o1-pro | Sonar Deep Research |
|---|---|---|---|---|
| Inputs & features | 60% | 0 | 70 | 10 |
| Context window | 40% | 0 | 32 | 24 |
| Overall | 100% | 0/100 | 55/100 | 16/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ALLaM-2-7bSDAIA | o1-proOpenAI | Sonar Deep ResearchPerplexity |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $150.00 | $2.00 (best) |
| Output | — | $600.00 | $8.00 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $262.50 | $3.50 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official OpenAI API | Official Perplexity API |
| Limits | |||
| Context window | 4,096 tokens | 200,000 tokens (best) | 128,000 tokens |
| Max output | 4,096 tokens | 100,000 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yeslow · medium · high | Yesminimal · low · medium · high |
| Tool calling | No | Yes | No |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | o1-pro | sonar-deep-research |
| API providers | 2 | 5 (best) | 3 |
| Released | Jan 23, 2025 | Mar 19, 2025 | Feb 1, 2025 |
| Knowledge cutoff | — | Sep 2023 | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- ALLaM-2-7b—
- o1-pro$2,700
- Sonar Deep Research$36.00
Which should you choose?
Which is better: ALLaM-2-7b, o1-pro or Sonar Deep Research?
o1-pro is the better all-round choice, scoring 55/100 against Sonar Deep Research (16) and ALLaM-2-7b (0). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, ALLaM-2-7b, o1-pro or Sonar Deep Research?
Sonar Deep Research is cheaper at $2.00 input / $8.00 output per million tokens (official Perplexity API price). o1-pro costs $150.00 input / $600.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $3.50 per million tokens for Sonar Deep Research versus $262.50 for o1-pro (75× as much). ALLaM-2-7b has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. ALLaM-2-7b has not been scored yet, o1-pro has not been scored yet and Sonar Deep Research has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for ALLaM-2-7b, o1-pro and Sonar Deep Research yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that ALLaM-2-7b and Sonar Deep Research does not support tool calling, which most coding agents need.
Which has the bigger context window?
o1-pro has the largest context window at 200,000 tokens, against 128,000 for Sonar Deep Research and 4,096 for ALLaM-2-7b. Maximum output per response: ALLaM-2-7b up to 4,096, o1-pro up to 100,000, Sonar Deep Research up to 32,768 tokens.
Which can read images, PDFs, audio or video?
ALLaM-2-7b accepts text; o1-pro accepts text and images; Sonar Deep Research accepts text. o1-pro handles the widest range of inputs.
Are any of these open source?
ALLaM-2-7b publishes its weights and can be self-hosted; o1-pro and Sonar Deep Research is proprietary.
Which is newer?
o1-pro is the newest, released Mar 19, 2025. Sonar Deep Research came out Feb 1, 2025; ALLaM-2-7b came out Jan 23, 2025. Knowledge cutoff: o1-pro Sep 2023, Sonar Deep Research Jan 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
