DeepSWE
No official DeepSWE mini-swe-agent row for this identity on the public board we fetched.
Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency....
Context window on the 2026-08-19 OpenRouter row: 262,144 tokens.
Max completion tokens on that row: 32,768.
Input / output on that row: $0.01 / $0.03 per 1M tokens.
Architecture fields: text->text · Other.
No hugging_face_id on the 2026-08-19 OpenRouter row.
Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficienc
When you want the 2026-04-21 catalog SKU, not a later rename.
No official DeepSWE mini-swe-agent row for this identity on the public board we fetched.
We did not open a vals.ai card for this identity. Chip omitted.
Ranked view: Best coding models: the independent leaderboard puts this row and every other card that carries an independent coding score on one board, with the confidence intervals left visible.
Copied from AA or vals HTML we opened. 0.0% placeholder bars are omitted. Do not average these into the hero tiles, and do not invent CI, $/task, or steps for Artificial Analysis.
| Bench | Printed | Note | Source | URL | As of |
|---|---|---|---|---|---|
| GDPval-AA v2 | 2.2% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
| τ³-Banking | 2.9% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
| Terminal-Bench v2.1 | 24.3% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
| SciCode | 27.1% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
| Humanity's Last Exam | 6.3% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
| GPQA Diamond | 59.3% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
| AA-Omniscience Accuracy | 15.6% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
| AA-LCR | 28% | Printed on the AA Intelligence Evaluations grid for Ling 2.6 Flash. Not a DeepSWE chip. | Artificial Analysis Ling 2.6 Flash | source | 2026-08-19 |
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Closed API SKU. The 2026-08-19 OpenRouter row lists pricing and context; there is no official Hugging Face weight dump on that row.
Lab card and OpenRouter listing only. No Hugging Face Files button, because there is no official repo to point at.
Fetched OpenRouter catalog on 2026-08-19. hugging_face_id was empty.
OpenRouter slug inclusionai/ling-2.6-flash on the 2026-08-19 catalog.
First party: https://huggingface.co/inclusionAI.
Not on the Continuum host list fetched 2026-08-19.
We list first-party and OpenRouter, plus Continuum only when the live public allowlist named the id. This is not a 15-host routing table.
OpenRouter 2026-08-19: $0.01 in / $0.03 out per 1M tokens. Context 262,144 in / 32,768 out.
No separate internal-reasoning price on that row.
| Claim | Source | As of |
|---|---|---|
| OpenRouter id inclusionai/ling-2.6-flash; context 262144; created 1776795886; $0.01 / $0.03 per 1M | OpenRouter /api/v1/models | 2026-08-19 |
| AA Intelligence Index 14; 8 printed Index benches | Artificial Analysis model page | 2026-08-19 |
| OpenRouter id inclusionai/ling-2.6-flash, context 262,144 | OpenRouter /api/v1/models | 2026-08-19 |
No other card in this cluster shares a published DeepSWE official row we can put next to this one. We will not compare on vendor-blog numbers.
Continue through InclusionAI's model family with Ling 3.0 Flash.
Lab posts pick a harness, an effort, a split, and sometimes a private eval set. DeepSWE publishes the official mini-swe-agent row with cost, tokens, and steps. Scale SWE-bench Pro only counts when the public shared-harness board has a row we can fetch. A higher lab number is usually a different test, not a better one.
No Continuum hosted id is verified for this model, so this page does not invent a curl target. Use the first-party API or the OpenRouter slug inclusionai/ling-2.6-flash.