Claude Mythos 5.1 vs Ling 3.0 Flash Sante vs GPT-6 Astra (Fast)
Too close to call on our weighted score (GPT-6 Astra (Fast) 66, Claude Mythos 5.1 66, Ling 3.0 Flash Sante 36). The right pick depends on what you value most.
AnthropicClaude Mythos 5.1
66/100- ECI—
- Price—
- Context1M
inclusionAILing 3.0 Flash Sante
36/100- ECI—
- Price$0.075 / $0.22
- Context262K
OpenAIGPT-6 Astra (Fast)
66/100- ECI—
- Price$20.00 / $100.00
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (GPT-6 Astra (Fast) 66/100, Claude Mythos 5.1 66/100, Ling 3.0 Flash Sante 36/100), so choose by what matters most for your work: Ling 3.0 Flash Sante on price and GPT-6 Astra (Fast) for long inputs. 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 priceLing 3.0 Flash SanteLing 3.0 Flash Sante $0.111 · GPT-6 Astra (Fast) $40.00 per 1M tokens (3:1 blend) · Claude Mythos 5.1 unpriced
- Longest contextGPT-6 Astra (Fast)GPT-6 Astra (Fast) 1,050,000 · Claude Mythos 5.1 1,000,000 · Ling 3.0 Flash Sante 262,144 tokens
- Widest inputsClaude Mythos 5.1 and GPT-6 Astra (Fast)Claude Mythos 5.1: Text, Images, PDFs · Ling 3.0 Flash Sante: Text · GPT-6 Astra (Fast): Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Claude Mythos 5.1 | Ling 3.0 Flash Sante | GPT-6 Astra (Fast) |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 35 | 70 |
| Context window | 40% | 60 | 37 | 61 |
| Overall | 100% | 66/100 | 36/100 | 66/100 |
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 | Claude Mythos 5.1Anthropic | Ling 3.0 Flash SanteinclusionAI | GPT-6 Astra (Fast)OpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $0.075 (best) | $20.00 |
| Output | — | $0.22 (best) | $100.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.111 (best) | $40.00 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 2 providers | Median of 1 providers |
| Limits | |||
| Context window | 1,000,000 tokens | 262,144 tokens | 1,050,000 tokens (best) |
| Max output | 128,000 tokens (best) | 32,768 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | — | — | — |
| API providers | — | 2 (best) | 1 |
| Released | Sep 1, 2026 | Sep 4, 2026 | Sep 4, 2026 |
| Knowledge cutoff | Jun 2026 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Mythos 5.1—
- Ling 3.0 Flash Sante$1.19
- GPT-6 Astra (Fast)$400.00
Which should you choose?
Which is better: Claude Mythos 5.1, Ling 3.0 Flash Sante or GPT-6 Astra (Fast)?
It is close. Our weighted score puts them within a point (GPT-6 Astra (Fast) 66/100, Claude Mythos 5.1 66/100, Ling 3.0 Flash Sante 36/100), so choose by what matters most for your work: Ling 3.0 Flash Sante on price and GPT-6 Astra (Fast) for long inputs. 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, Claude Mythos 5.1, Ling 3.0 Flash Sante or GPT-6 Astra (Fast)?
Ling 3.0 Flash Sante is cheaper at $0.075 input / $0.22 output per million tokens (median across 2 API providers). GPT-6 Astra (Fast) costs $20.00 input / $100.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.111 per million tokens for Ling 3.0 Flash Sante versus $40.00 for GPT-6 Astra (Fast) (360× as much). Claude Mythos 5.1 has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Claude Mythos 5.1 has not been scored yet, Ling 3.0 Flash Sante has not been scored yet and GPT-6 Astra (Fast) has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Mythos 5.1, Ling 3.0 Flash Sante and GPT-6 Astra (Fast) yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-6 Astra (Fast) has the largest context window at 1,050,000 tokens, against 1,000,000 for Claude Mythos 5.1 and 262,144 for Ling 3.0 Flash Sante. Maximum output per response: Claude Mythos 5.1 up to 128,000, Ling 3.0 Flash Sante up to 32,768, GPT-6 Astra (Fast) up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Claude Mythos 5.1 accepts text, images and PDFs; Ling 3.0 Flash Sante accepts text; GPT-6 Astra (Fast) accepts text, images and PDFs. Claude Mythos 5.1 handles the widest range of inputs.
Are any of these open source?
No. Claude Mythos 5.1, Ling 3.0 Flash Sante and GPT-6 Astra (Fast) are proprietary and only available through APIs and apps.
Which is newer?
Ling 3.0 Flash Sante is the newest, released Sep 4, 2026. GPT-6 Astra (Fast) came out Sep 4, 2026; Claude Mythos 5.1 came out Sep 1, 2026. Knowledge cutoff: Claude Mythos 5.1 Jun 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.
