Qwen3.5 122B-A10B vs Sarvam 105B
Too close to call on our weighted score (Qwen3.5 122B-A10B 54, Sarvam 105B 52). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3.5 122B-A10B
54/100- ECI—
- Price$0.40 / $3.20
- Context262K
Sarvam AI
Sarvam 105B
52/100- ECI—
- Price$0.158 / $0.632
- Context131K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (Qwen3.5 122B-A10B 54/100, Sarvam 105B 52/100), so choose by what matters most for your work: Sarvam 105B on price and Qwen3.5 122B-A10B for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. 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 priceSarvam 105BSarvam 105B $0.276 · Qwen3.5 122B-A10B $1.10 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 122B-A10BQwen3.5 122B-A10B 262,144 · Sarvam 105B 131,072 tokens
- Widest inputsQwen3.5 122B-A10BQwen3.5 122B-A10B: Text, Images, Video · Sarvam 105B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3.5 122B-A10B | Sarvam 105B |
|---|---|---|---|
| Price | 50% | 46 | 73 |
| Inputs & features | 30% | 80 | 35 |
| Context window | 20% | 37 | 25 |
| Overall | 100% | 54/100 | 52/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.5 122B-A10BAlibaba (Qwen) | Sarvam 105BSarvam AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.40 | $0.158 (best) |
| Output | $3.20 | $0.632 (best) |
| Cached input | — | $0.053 |
| Blended (3:1) | $1.10 | $0.276 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Sarvam AI API |
| Limits | ||
| Context window | 262,144 tokens (best) | 131,072 tokens |
| Max output | 65,536 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yes | Yeslow · medium · high |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | qwen3.5-122b-a10b | sarvam-105b |
| API providers | 22 (best) | 3 |
| Released | Feb 23, 2026 | Feb 18, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.5 122B-A10B$10.40
- Sarvam 105B$2.84
Which should you choose?
Which is better: Qwen3.5 122B-A10B or Sarvam 105B?
It is close. Our weighted score puts them within 2 points (Qwen3.5 122B-A10B 54/100, Sarvam 105B 52/100), so choose by what matters most for your work: Sarvam 105B on price and Qwen3.5 122B-A10B for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen3.5 122B-A10B or Sarvam 105B?
Sarvam 105B is cheaper at $0.158 input / $0.632 output per million tokens (official Sarvam AI API price). Qwen3.5 122B-A10B costs $0.40 input / $3.20 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.276 per million tokens for Sarvam 105B versus $1.10 for Qwen3.5 122B-A10B (4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Qwen3.5 122B-A10B has not been scored yet and Sarvam 105B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 122B-A10B and Sarvam 105B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.5 122B-A10B has the largest context window at 262,144 tokens, against 131,072 for Sarvam 105B. Maximum output per response: Qwen3.5 122B-A10B up to 65,536, Sarvam 105B up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 122B-A10B accepts text, images and video; Sarvam 105B accepts text. Qwen3.5 122B-A10B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Qwen3.5 122B-A10B is the newest, released Feb 23, 2026. Sarvam 105B came out Feb 18, 2026.
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 Nov 2, 2026.
