Sarvam 105B vs GLM-4.6V-Flash
GLM-4.6V-Flash comes out ahead, 63 to 52 on our weighted score, and it is the cheaper option too.
Sarvam AI
Sarvam 105B
52/100- ECI—
- Price$0.158 / $0.632
- Context131K
- Our pick
Z.ai (Zhipu)GLM-4.6V-Flash
63/100- ECI—
- Price$0.161 / $0.559
- Context128K
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Make it a three-way comparison.
GLM-4.6V-Flash is our pick
GLM-4.6V-Flash is the better all-round choice, scoring 63/100 against Sarvam 105B (52). It leads on inputs & features. 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 priceGLM-4.6V-FlashGLM-4.6V-Flash $0.261 · Sarvam 105B $0.276 per 1M tokens (3:1 blend)
- Longest contextSarvam 105BSarvam 105B 131,072 · GLM-4.6V-Flash 128,000 tokens
- Widest inputsGLM-4.6V-FlashSarvam 105B: Text · GLM-4.6V-Flash: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Sarvam 105B | GLM-4.6V-Flash |
|---|---|---|---|
| Price | 50% | 73 | 74 |
| Inputs & features | 30% | 35 | 70 |
| Context window | 20% | 25 | 24 |
| Overall | 100% | 52/100 | 63/100 |
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 | Sarvam 105BSarvam AI | GLM-4.6V-FlashZ.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.158 (best) | $0.161 |
| Output | $0.632 | $0.559 (best) |
| Cached input | $0.053 | — |
| Blended (3:1) | $0.276 | $0.261 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Sarvam AI API | Median of 2 providers |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | Yes |
| Reasoning | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | sarvam-105b | glm-4.6v-flash |
| API providers | 3 | 6 (best) |
| Released | Feb 18, 2026 | Dec 8, 2025 |
| 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.
- Sarvam 105B$2.84
- GLM-4.6V-Flash$2.73
Which should you choose?
Which is better: Sarvam 105B or GLM-4.6V-Flash?
GLM-4.6V-Flash is the better all-round choice, scoring 63/100 against Sarvam 105B (52). It leads on inputs & features. 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, Sarvam 105B or GLM-4.6V-Flash?
GLM-4.6V-Flash is cheaper at $0.161 input / $0.559 output per million tokens (median across 2 API providers; free on Z.AI). Sarvam 105B costs $0.158 input / $0.632 output per million tokens (official Sarvam AI API price). At a typical mix of three input tokens to one output token, that is $0.261 per million tokens for GLM-4.6V-Flash versus $0.276 for Sarvam 105B (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Sarvam 105B has not been scored yet and GLM-4.6V-Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Sarvam 105B and GLM-4.6V-Flash 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?
Sarvam 105B has the largest context window at 131,072 tokens, against 128,000 for GLM-4.6V-Flash. Maximum output per response: Sarvam 105B up to 131,072, GLM-4.6V-Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Sarvam 105B accepts text; GLM-4.6V-Flash accepts text, images and video. GLM-4.6V-Flash 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?
Sarvam 105B is the newest, released Feb 18, 2026. GLM-4.6V-Flash came out Dec 8, 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 Nov 2, 2026.
