Model Comparison
105B (high)
vs. M (Reasoning)
Comparing 2 AI models · 11 benchmarks · Sarvam
Recommended Pick
Sa105B (high)8 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
M (Reasoning)
$0.00/1M input price
Best Reasoning
105B (high)
31.9 reasoning score
Blends available reasoning benchmarks
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
M (Reasoning) is ∞x cheaper on input tokens than 105B (high).
Reasoning gap
105B (high) leads M (Reasoning) by 1.3 points on reasoning.
Top-pick rationale
105B (high) wins 8 measurable categories, including Throughput, Reasoning, Intelligence, GPQA.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
105B (high)
Sarvam
TTFT
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Time
—
tok/s
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Tokens
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Cost
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M (Reasoning)
Sarvam
TTFT
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Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Top Pick Sa 105B (high) | Sa M (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.04/1M | $0.00/1M |
| Output Cost | $0.17/1M | $0.00/1M |
| Blended (3:1) | $0.07/1M | — |
| Specifications | ||
| Organization | Sarvam | Sarvam |
| Release Date | Mar 6, 2026 | May 23, 2025 |
| Performance & Speed | ||
| Throughput | 112.8 tok/s | — |
| TTFT | 1195ms | — |
| Latency | 18924ms | — |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 31.9 | 30.6 |
| Intelligence | 11.9 | 3.0 |
| Standard Benchmarks | ||
| GPQA | 73.8% | 41.6% |
| MMLU Pro | — | 69.6% |
| HLE | 10.1% | 3.3% |
| LiveCodeBench | — | 29.5% |
| MATH 500 | — | 84.7% |
| AIME (Original) | — | 20.3% |
| SciCode | 26.4% | 17.8% |
| LCR | 0.0% | 0.0% |
| IFBench | 34.4% | 31.8% |
| TAU-bench v2 | 46.8% | 0.0% |
| TerminalBench Hard | 1.5% | 2.3% |
Key Takeaways
M (Reasoning) offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
105B (high) has the strongest reasoning profile with a 31.9 reasoning score,combining the available reasoning-heavy benchmarks.
All models support context windows of ∞+ tokens,suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
105B (high)
- Complex reasoning tasks
- Research & analysis
M (Reasoning)
- Cost-sensitive applications
- High-volume processing
